Alfredo
Vellido / publications
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type (books & chapters, journals,
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research area (theory, medical, business, ...)
2019
Vellido, A. The importance of interpretability and
visualization in Machine Learning for applications in
medicine and health care. Neural Computing &
Applications, accepted. draft.
2018
Bilal,
A., Vellido, A., Ribas, V. Enabling
interpretation of the outcome of a human obesity
prediction machine learning analysis from genomic data.
In procs. of the 15th International Conference on
Computational Intelligence methods for Bioinformatics
and Biostatistics (CIBB
2018) Lisbon,
Portugal.
Ribas Ripoll, V., Vellido, A, Blood pressure assessment with differential pulse transit time and deep learning: a proof of concept. Kidney Diseases; DOI: 10.1159/000493478
Hueso
M, Vellido A, Artificial
Intelligence and Dialysis.
Kidney Diseases;
DOI:
10.1159/000493933
Vellido A,
Societal Issues Concerning the
Application of Artificial Intelligence
in Medicine. Kidney Diseases,
free
access
https://doi.org/10.1159/000492428.
König,
C., Shaim, I. , Vellido, A., Romero, E., Alquézar, R.,
Giraldo, J. Using
machine learning tools for protein database
biocuration assistance, Scientific Reports,
8:10148.
Bacciu,
D., Lisboa, P.J., Martín, J.D., Stoean, R. and Vellido,
A. Bioinformatics
and medicine in the era of Deep Learning. In
Proceedings of the 26th European Symposium on Artificial
Neural Networks, Computational Intelligence and Machine
Learning (ESANN 2018), Bruges, Belgium,
pp.345-354.
Bilal,
A., Vellido, A., Ribas, V. Big data analytics for
obesity prediction. In 21st International
Conference of the Catalan Association for Artificial
Intelligence (CCIA
2018) Roses,
Spain. Accepted.
Hueso M, Vellido A, Montero N, Barbieri C, Ramos R, Angoso M, Cruzado JM, Jonsson A, Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy. Kidney Diseases; 4:1-9. open access.
Vellido
A, Ribas V, Subirats L, Morales C, Ruiz Sanmartín A,
Ruiz Rodríguez JC, Machine
Learning for Critical Care: State-of-the-Art and a
Sepsis Case Study, BioMedical Engineering
OnLine, 17(S1):135.
König
C, Alquézar R, Vellido A, Giraldo J, Systematic analysis
of primary sequence domain segments for the
discrimination between class C GPCR subtypes, Interdisciplinary
Sciences: Computational Life Sciences,
10(1), 43-52.
2017
Y. Hernández–Villegas, V. Mocioiu, D. Ulinic, S.P. Kyathanahally, A. Vellido, C. Arús, M. Julià-Sapé. Automated quality control of magnetic resonance spectra of brain tumors by Convex Non-negative Matrix Factorization. In 34th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB), Barcelona, Spain, 2017
A. Shkurin, A. Vellido, Using random forests for assistance in the curation of G-protein coupled receptor databases. BioMedical Engineering OnLine, 16(Suppl 1):75
C.
König, R. Alquézar, A. Vellido, J. Giraldo. Discovering
subtype specific n-gram motifs in class C GPCR
N-termini. In Recent Advances in
Artificial Intelligence Research and Development:
Proceedings of the 20th International Conference of the
Catalan Association for Artificial Intelligence,
Deltebre, Terres de L'Ebre, Spain, October 25-27, 2017
(Vol. 300, p. 116). IOS Press.
A.
Vellido, D.L. García. Electricity rate planning for the
current consumer market scenario through segmentation of
consumption time series. In Artificial Intelligence in
Power and Energy Systems (AIPES) 18th
EPIA Conference on Artificial Intelligence,
Porto, Portugal, LNCS 10423, pp.
295-306, Springer
D.L. García, À.
Nebot, A. Vellido. Intelligent data analysis approaches
to churn as a business problem: a survey. Knowledge
and Information Systems, 51(3):719-774. doi:
10.1007/s10115-016-0995-z (draft)
X.
Cipriano, A. Vellido, J. Cipriano, J. Martí, S. Danov.
Application of clustering and simulation methods for the
analysis of socio-economical and technical factors
influencing the energy refurbishment of neighbourhoods.
Energy Efficiency, 10(2), 359-382. doi:
10.1007/s12053-016-9460-9
C.
König, R. Alquézar, A. Vellido, J. Giraldo. Topological
sequence segments discriminate between class C GPCR
subtypes. In 11th
International Conference on Practical Applications of
Computational Biology & Bioinformatics (PACBB
2017), Porto, Portugal. Accepted
A.
Vellido, V. Ribas, C. Morales, A. Ruiz Sanmartín, J.C.
Ruiz-Rodríguez. Machine Learning for Critical Care: An
Overview and a Sepsis Case Study. In I. Rojas
and F. Ortuño (Eds.): Procs.
of the 5th International
Work-Conference on Bioinformatics and Biomedical
Engineering (IWBBIO
2017), Granada, Spain. Part I, LNBI 10208,
pp.15-30, Springer. doi: 10.1007/978-3-319-56148-6 2.
2016
C.
Morales, A. Vellido, V. Ribas. Applying Conditional
Independence Maps to improve Sepsis Prognosis. Data
Mining in Biomedical Informatics and Healthcare (DMBIH)
Workshop. IEEE International Conference on Data Mining (ICDM
2016)
J.R.G.
Cárdenas, À. Nebot, F. Mugica, A. Vellido. A decision
making support tool: The Resilience Management Fuzzy
Controller, In 2016 IEEE
Congress on Evolutionary
Computation (CEC / WCCI'16),
pp.2313-2320.
I. Paz, À. Nebot, E. Romero, F. Mugica and A. Vellido: A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration, In 2016 IEEE Congress on Evolutionary Computation (CEC / WCCI'16), pp.1317-1323.
E. Racec, S. Budulan, and A. Vellido. Computational Intelligence in architectural and interior design: a state-of-the-art and outlook on the field. In Artificial Intelligence Research and Development: Proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2016), Barcelona, Spain, Vol. 288, p.108. IOS Press. [draft]
M.I.
Cárdenas, A. Vellido and J. Giraldo, Visual exploratory
assessment of class C GPCR extracellular domains
discrimination capabilities, In Procs. of the 10th
International Conference on Practical Applications of
Computational Biology & Bioinformatics (PACBB'16)
Advances in Intelligent
Systems and Computing series, Vol.477,
Springer, pp.31-39.
J.D.
Martín-Guerrero, J.P.G. Lisboa, A. Vellido, Physics and
Machine Learning: Emerging Paradigms. In
Proceedings of the 24th European Symposium
on Artificial Neural Networks,
Computational Intelligence and Machine
Learning (ESANN 2016),
Bruges, Belgium,
pp.319-326. [draft]
V.
Mocioiu, N.M. Pedrosa de Barros, S. Ortega-Martorell,J.
Slotboom, U. Knecht, C. Arús, A. Vellido and M.
Julià-Sapé. A machine learning pipeline for supporting
differentiation of glioblastomas from single brain
metastases, In
Proceedings of the 24th European Symposium
on Artificial Neural Networks,
Computational Intelligence and Machine
Learning (ESANN 2016),
Bruges, Belgium, pp.247-252. .
A.
Vilamala, A. Vellido, L. Belanche, Bayesian Semi
Non-negative Matrix Factorisation. In Proceedings of the
24th European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN
2016), Bruges, Belgium. pp.195-200.
V. Mocioiu, S.P. Kyathanahally, C. Arús, A. Vellido, M. Julià-Sapé, Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization, In Bioinformatics and Biomedical Engineering (F. Ortuño, I.Rojas, eds.) Proceedings of the 4th International Conference, IWBBIO 2016, Granada, Spain, April 20-22, 2016, LNCS/LNBI 9656, pp 719-727
A.
Shkurin and A. Vellido, Random Forests for quality
control in G-Protein Coupled Receptor databases, In Bioinformatics
and Biomedical Engineering (F. Ortuño, I.Rojas,
eds.) Proceedings of the 4th International Conference, IWBBIO
2016, Granada, Spain, April 20-22, 2016, LNCS/LNBI
9656, pp 707-718.
2015
C.L.
König, M.I. Cárdenas, J. Giraldo, R. Alquezar, A.
Vellido. Label noise in subtype discrimination of class
C G-protein coupled receptors: A systematic
approach to the analysis of classification errors. BMC
Bioinformatics, 16(1):314. open
access
P.J.G. Lisboa,
J.D. Martín,
and A. Vellido,
Making Nonlinear Manifold Learning Models Interpretable:
the Manifold Grand Tour. Expert Systems with
Applications, 42(22), 8982-8988.
M.I.
Cárdenas, A. Vellido, C. König, R. Alquézar and J.
Giraldo, Visual Characterization of Misclassified Class
C GPCRs through Manifold-based Machine Learning Methods.
Genomics and Computational Biology, 1(1),
e19. open
access.
C
König, R Alquézar, A Vellido, J Giraldo: The
Extracellular N-terminal Domain Suffices to Discriminate
Class C G Protein-Coupled Receptor Subtypes from
n-Grams of their Sequences, In: Procs. of the
International Joint-Conference on Artificial Neural
Networks (IJCNN 2015), Killarney,
Ireland, pp.2330-2336.
A.
Vellido, C. Halka, À. Nebot. A Weighted Cramer's V
Index for the Assessment of Stability in the Fuzzy
Clustering of Class C G
Protein-Coupled Receptors. In F. Ortuño and I. Rojas
(Eds.): IWBBIO 2015, Part I, LNCS 9043, pp.
536--547, Springer
R.
Cruz-Barbosa, A. Vellido, J. Giraldo. The influence of
alignment-free sequence representations on the
semi-supervised classication of Class C G
Protein-Coupled Receptors. Medical &
Biological Engineering & Computing,
53(2), 137-149, available
online
from Nov 2014.
2014
C.
König, R. Alquézar, A. Vellido and J. Giraldo. Finding
class C GPCR subtype-discriminating n-grams through
feature selection. Journal of Integrative
Bioinformatics, 11(3):254.
doi: 10.2390/biecoll-jib-2014-254.
A.
Tosi, A. Vellido, Probabilistic Geometries as a tool for
Interpretability in Dimensionality Reduction Models, In
the 8th WiML Workshop, Advances in Neural
Information Processing Systems (NIPS 2014), Montreal, Canada.
A.
Tosi, S. Hauberg, A. Vellido, N. Lawrence. Metrics for
probabilistic geometries, In Nevin L. Zhang, Jin
Tian (eds.) Proceedings of The 30th Conference on
Uncertainty in
Artificial Intelligence (UAI
2014),
AUAI Press Corvallis, Oregon, USA, pp.800-808.
M.I.
Cárdenas, A. Vellido, J. Giraldo. Exploratory
visualization of Metabotropic Glutamate Receptor
subgroups through manifold learning. 17th
International Conference of the Catalan Association of
Artificial Intelligence (CCIA 2014) In L. Museros
et al. (Eds.) Artificial
Intelligence Research and Development, IOS Press, pp.269-272.
A.
Vilamala, Ll. Belanche, A. Vellido. A MAP approach for
Convex Non-negative Matrix Factorization in the
Diagnosis of Brain Tumors. 4th International
Workshop on Pattern Recognition in Neuroimaging (PRNI
2014) pp.1-4 doi: 10.1109/PRNI.2014.6858550
A.
Tosi and A. Vellido. Local metric and graph based
distance for probabilistic dimensionality reduction. The
workshop on Features and Structures (FEAST 2014)
International Conference on Pattern Recognition (ICPR
2014), Stockholm, Sweden. (best
poster award)
C.
König, R. Alquézar, A. Vellido, Finding class C GPCR
subtype-discriminating n-grams through feature
selection, In Procs. of the 8th International
Conference on Practical Applications of Computational
Biology & Bioinformatics (PACBB 2014), pp.89-96.
M.I.
Cárdenas, A. Vellido, J. Giraldo, Visual interpretation
of class C GPCR subtype overlapping from the nonlinear
mapping of transformed primary sequences. In Procs. of
the 2nd International Conference on
Biomedical and Health Informatics (IEEE BHI'14)
pp.764-767.
V.J. Ribas Ripoll, A. Wojdel, A. Sáez de Tejada Cuenca,
J.C. Ruiz-Rodríguez, A. Ruiz-Sanmartín, M. de Nadal, E.
Romero, A. Vellido,
Continuous blood pressure assessment from a
photoplethysmographic signal with Deep Belief Networks,
The FASEB Journal, 28(1),
Supplement LB674.
V. Ribas, A. Vellido, E. Romero and J.C. Ruiz-Rodríguez. Sepsis Mortality Prediction with Quotient Basis Kernels. Artificial Intelligence in Medicine, 61(1), 45-52. DOI:10.1016/j.artmed.2014.03.004
M.I. Cárdenas, A. Vellido, C. König, R. Alquézar and J. Giraldo, Exploratory visualization of misclassified GPCRs from their transformed unaligned sequences using manifold learning techniques, In F. Ortuño, I. Rojas (eds.): Procs. of the 2nd International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2014) pp.623-630.
A. Tosi, I. Olier, A. Vellido, Probability ridges and distortion flows: Visualizing multivariate time series using a variational Bayesian manifold learning method. 10th Workshop on Self-Organizing Maps (WSOM 2014). Advances in Intelligent Systems and Computing, Vol.295, pp.55-64.
C.
Arizmendi, D.A. Sierra, A. Vellido and E.Romero.
Automated classification of brain tumours from short
echo time in vivo MRS data
using Gaussian decomposition
and Bayesian Neural Networks, Expert Systems with
Applications, 41(11), 5296-5307.
doi: http://dx.doi.org/10.1016/j.eswa.2014.02.031.
König,
C., Vellido, A., Alquézar, R. and Giraldo, J.
Misclassification of class C G-protein-coupled receptors
as a label noise problem. In Proceedings of the 22nd
European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN 2014),
Bruges, Belgium. pp. 695-700.
2013
Ortega-Martorell, S., Ruiz,
H., Vellido, A., Olier, I., Romero, E.,
Julià-Sapé, M., Martín, J.D.
, Jarman, I.H.,
Arús, C.,
Lisboa, P.J.G.
A novel semi-supervised methodology for
extracting tumor type-specific MRS sources in
human brain data, PLoS ONE,
8(12), 2013: e83773
Vilamala,
A., Lisboa, P.J.G., Ortega-Martorell,
S., Vellido, A.
Discriminant
Convex Non-negative Matrix Factorization for the
Classification of Human Brain
Tumours, Pattern Recognition Letters,
34(14), 1734–1747.
Cruz-Barbosa, R.
and Vellido, A. Generative manifold learning for the
exploration of partially labeled data. Computación
& Sistemas, 17(4), 641-653. doi:
10.13053/CyS-17-4-2013-014
Martín, À, Vellido,
A.
Cartogram-based data visualization using the Growing
Hierarchical SOM, In K. Gibert, V. Botti and R.
Reig-Bolaño (eds.) Artificial Intelligence Research
and Development. Procs. of the 16th International
Conference of the Catalan Association for Artificial
Intelligence (CCIA 2013), pp.249-252, IOS Press.
König, C., Cruz-Barbosa, R., Alquézar, R. and Vellido, A. SVM-Based Classification of Class C GPCRs from Alignment-Free Physicochemical Transformations of Their Sequences. 2nd International Workshop on Pattern Recognition in Proteomics, Structural Biology and Bioinformatics (PR PS BB 2013), 17th International Conference on Image Analysis and Processing (ICIAP) In A. Petrosino, L. Maddalena, P. Pala (Eds.): ICIAP 2013 Workshops, LNCS 8158, pp. 336–343, 2013, Springer.
Cruz-Barbosa, R.,
Vellido, A., Giraldo, J. Advances
in Semi-Supervised Alignment-Free Classification of
G-Protein-Coupled Receptors, In Procs. of the
International Work-Conference on Bioinformatics and
Biomedical Engineering (IWBBIO'13), Granada, Spain,
pp.759-766.
Ribas Ripoll, V.,
Romero, E., Ruiz-Rodríguez, J.C., Vellido,
A. A Quotient Basis Kernel for the prediction of mortality
in severe sepsis patients. In Proceedings of the 21st European Symposium on
Artificial Neural Networks, Computational Intelligence and
Machine Learning (ESANN
2013), Bruges,
Belgium, pp.379-384.
Tosi, A., Vellido,
A. Robust cartogram visualization of outliers in manifold
learning, In Proceedings of the 21st
European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN 2013), Bruges,
Belgium, pp.555-560.
García, D.L., Nebot, À. Vellido,
A.
Visualizing pay-per-view television customers churn using
cartograms and flow maps, In Proceedings of the 21st
European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN 2013), Bruges,
Belgium, pp.567-572.
Garcia, D.L.,
Vellido, A., Nebot, À. Telecommunication Customers
Churn Monitoring Using Flow Maps and Cartogram
Visualization. In GRAPP 2013 / IVAPP 2013 -
Proceedings of the International Conference on Computer
Graphics Theory and Applications and International
Conference on Information Visualization Theory and
Applications, pp.451-460, Barcelona, Spain
Vellido, A., García,
D.,Nebot, À. Cartogram Visualization for Nonlinear
Manifold Learning Models. Data Mining and
Knowledge Discovery, 27(1):22-54.
doi: 10.1007/s10618-012-0294-6
2012
Biganzoli,
E., Vellido, A., Ambrogi, F., Tagliaferri, R. (Editors)
Computational Intelligence Methods for Bioinformatics and
Biostatistics, LNBI/LNCS
7548, 2012.
P.J.G. Lisboa, I.H.
Jarman, T.A. Etchells, S.J. Chambers, D. Bacciu, J.
Whittaker, J.M. Garibaldi, S. Ortega-Martorell, A.
Vellido, I.O. Ellis. Discovering Hidden Pathways in
Bioinformatics, LNCS/LNBI 7548, pp 49-60
V.J. Ribas, J.
Caballero López, A. Sáez de Tejada, J.C. Ruiz-Rodríguez,
A. Ruiz-Sanmartín, J. Rello, A. Vellido. On the Use of
Graphical Models to Study ICU Outcome Prediction in Septic
Patients Treated with Statins, LNCS/LNBI 7548, pp
98-111
M.I. Cárdenas, A.
Vellido, I. Olier, X. Rovira, J. Giraldo. Complementing
Kernel-Based Visualization of Protein Sequences with Their
Phylogenetic Tree, LNCS/LNBI 7548, pp 136-149
Ortega-Martorell, S., Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. Convex Non-Negative Matrix Factorization for Brain Tumor Delimitation from MRSI Data, PLoS ONE, 7(10):e47824.
Ortega-Martorell,
S., Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M.,
Julià-Sapé, M., Arús, C. Unsupervised tumour area delimitation
in glioblastoma multiforme using non-negative matrix
factorisation of MRSI grids. European Society for Magnetic
resonance in Medicine and Biology Congress (ESMRMB 2012). Accepted for
oral presentation.
Ortega-Martorell,
S., Lisboa, P.J.G., Vellido, A.,Julià-Sapé, M., Arús, C. Non-negative Matrix
Factorisation methods for the spectral decomposition of MRS
data from human brain tumours. BMC Bioinformatics, 13:38.
(draft)
Vellido, A., Romero, E., Julià-Sapé, M., Majós, C., Moreno-Torres, À., and Arús, C. Robust discrimination of glioblastomas from metastatic brain tumors on the basis of single-voxel proton MRS. NMR in Biomedicine. 25(6):819–828. (draft)
Ribas, V.J., Vellido, A., Ruiz-Rodríguez, J.C., Rello, J. Severe sepsis mortality prediction with logistic regression over latent factors. Expert Systems with Applications, 39(2), 1937-1943. (draft)
Arizmendi, C., Vellido, A., Romero, E. Classification of human brain tumours from MRS data using discrete wavelet transform and Bayesian neural networks. Expert Systems with Applications, 39(5), 5223-5232.
Arizmendi,
C.J.,
Vellido,
A., Romero, E. Preprocessing MRS Information for
Classification of Human Brain Tumours. In: R.
Magdalena-Benedito, E. Soria, J. Guerrero Martínez, J.
Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.29-49, doi: 10.4018/978-1-4666-1803-9.ch003
Cárdenas, M.I., Vellido, A., Olier, I., Rovira, X., Giraldo, J. Kernel Generative Topographic Mapping of Protein Sequences. In: R. Magdalena-Benedito, E. Soria, J. Guerrero Martínez, J. Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of Intelligent Data Analysis: Research Advancements, IGI Global, 2012, pp.194-207, doi: 10.4018/978-1-4666-1803-9.ch013
V.J.Ribas, J.C. Ruiz-Rodríguez and A. Vellido,
Intelligent management of sepsis in the intensive care unit,
In: R. Magdalena-Benedito, E. Soria, J. Guerrero Martínez,
J. Gómez-Sanchis and A.J. Serrano-López (eds.)
Medical Applications of Intelligent Data Analysis:
Research Advancements, IGI Global, 2012, pp.1-16,
doi:10.4018/978-1-4666-1803-9.ch001
Tosi,
A., Vellido, A. Cartogram representation of the
batch-SOM magnification factor. In Proceedings of the
European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN 2012),
Bruges, Belgium, pp.203-208.
Vellido,
A., Martín-Guerrero, J.D., Lisboa, P.J.G. Making machine learning
models interpretable.
In Proceedings of
the European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning ( ESANN 2012),
Bruges, Belgium, pp.163-172.
Ortega-Martorell, S. Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. Delimitation of the solid tumour area in glioblastomas using Non-Negative Matrix Factorization, In Procs. of the IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012), abstract.
Vilamala, A., Belanche, L.A., and Vellido, A. Classifying malignant brain tumours from 1H-MRS data using Breadth Ensemble Learning. In Procs. of the IEEE World Congress on Computational Intelligence (WCCI 2012) International Joint Conference on Artificial Neural Networks (IJCNN 2012), Brisbane, Australia, pp.2803-2810.
Ruiz,
H., Ortega-Martorell, S., Jarman, I.H., Vellido, A., Romero,
E., Martín, J.D. and Lisboa, P.J.G. Towards Interpretable Classifiers with
Blind Signal Separation. In Procs. of the IEEE World Congress on
Computational Intelligence (WCCI 2012) International Joint
Conference on Artificial Neural Networks (IJCNN 2012), Brisbane,
Australia, 3008-3016.
2011
Ortega-Martorell, S., Lisboa, P.J.G., Vellido, A., Simões,
R.V., Julià-Sapé, M., and Arús, C. Brain tumor pathological
area delimitation through Non-negative Matrix Factorization,
BioDM' Workshop, The IEEE 11th International Conference on Data
Mining Workshops (ICDMW'11)
pp.1058-1063
Cruz-Barbosa,
R., Bautista-Villavicencio, D., Vellido, A. On the computation
of the Geodesic Distance with an application to dimensionality
reduction in a neuro-oncology problem. In Procs. of The 16th
Iberoamerican Congress on Pattern Recognition (CIARP 2011), LNCS 7042, pp.483-490.
Ribas,
V., Ruiz-Rodríguez, J.D., Wojdel, A., Caballero-López, J.,
Ruiz-Sanmartín A., Rello, J. and Vellido, A. Severe
sepsis mortality prediction with Relevance Vector Machines. In
Procs. of the 33rd Annual International Conference
of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp.100-103.
Arizmendi, C., Sierra, D.A., Vellido, A., Romero, E. Brain Tumour Classification Using Gaussian Decomposition and Neural Networks. In Procs. of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp.5645-5648.
Ortega-Martorell,
S., Olier, I., Vellido, A., Lisboa, P.J.G., El-Deredy, W. Comparing independent component
analysis and non-negative matrix factorisation in the
identification of event-related brain dynamics, 11th International
Conference on Cognitive Neuroscience (ICON XI), Abstract A066,
p.82.
Ortega-Martorell, S., Vellido, A., Lisboa, P.J.G., Julià-Sapé, M., and Arús, C. Spectral
decomposition methods for the analysis of MRS information from
human brain tumours, In Procs. of the 2011 International Joint
Conference on Neural Networks (IJCNN 2011), pp.3285-3292.
Cárdenas,
M.I., Vellido, A., Olier, I., Rovira, X., Giraldo, J.
Visualization of the phylogenetic structure of G
Protein-Coupled Receptor sequences using kernel and tree
methods, Eigth International Meeting on Computational
Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011)
Ribas, V.J., Caballero-López, J., Saez de Tejada, A., Ruiz-Rodríguez, J.C., Ruiz-Sanmartín, A., Rello, J., Vellido, A. Bayesian networks
for ICU outcome prediction in sepsis patients treated with
statin drugs, Eigth International Meeting on Computational
Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011).
Lisboa, P.J.G., Jarman, I.H., Etchells, T.A. , Chambers, S.J., Bacciu, D., Whittaker, J., Garibaldi, J. M., Ortega-Martorell, S., Vellido, A., and Ellis, I.H. Discovering hidden pathways in bioinformatics, Eigth International Meeting on Computational Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011).
Arizmendi,
C., Vellido, A., Romero, E., Binary Classification of Brain
Tumours Using a Discrete Wavelet Transform and Energy
Criteria, In Procs. of the 2nd IEEE Latin American
Symposium on Circuits and Systems (LASCAS 2011), pp.1-4.
Vellido,
A., Cárdenas, M.I., Olier, I., Rovira, X., and Giraldo,
J. A probabilistic approach to the visual exploration of
G Protein-Coupled Receptor sequences, In Procs. of the 19th European Symposiun
on Artificial Neural Networks (ESANN 2011), pp.233-238.
Vellido, A., Martín, J.D.,
Rossi, F., and Lisboa, P.J.G. Seeing is believing: The importance of
visualization in real-world machine learning applications, In Procs. of the 19th European Symposiun
on Artificial Neural Networks (ESANN 2011), pp.219-226.
Cruz-Barbosa,
R., Bautista-Villavicencio, D., and Vellido, A. Comparative
diagnostic accuracy of linear and nonlinear feature extraction
methods in a neuro-oncology problem. In Procs. of the 3rd
Mexican Conference on Pattern Recognition (MCPR 2011) LNCS, Vol.6718, 2011,
pp.34-41.
Ribas,
V.,
Caballero-López, J., Ruiz-Rodríguez, J.C., Ruiz Sanmartín, A.,
Rello, J., and Vellido, A. On the use of decision trees for ICU
outcome prediction in sepsis patients treated with statins. In
Procs. of the IEEE Symposium Series on Computational
Intelligence / IEEE Symposium on Computational Intelligence
and Data Mining (IEEE SSCI
CIDM 2011), pp.37-43.
Olier, I., Amengual, J. and Vellido, A. A variational Bayesian approach for the robust estimation of cortical silent periods from EMG time series of brain stroke patients. Neurocomputing, 74(9): 1301-1314.
Cruz,
R., Vellido, A., Semi-supervised analysis of human brain
tumours from partially labeled MRS information, using manifold
learning models. International Journal of Neural Systems.
21(1): 17-29.
2010
Vellido,
A. Should you trust what you see? Inroads into data
visualization using generative topographic mapping. 3rd
International Conference of the ERCIM WG on Computing &
Statistics (ERCIM 2010),
London, U.K.
Arizmendi,
C., Hernández-Tamames, J., Romero, E., Vellido, A., del Pozo,
F., Diagnosis of Brain Tumours from Magnetic Resonance
Spectroscopy using Wavelets and Neural Networks. In Procs. of the 32nd
Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBC
2010) Buenos Aires, Argentina, pp.6074-6077
Colas,
F., Kok, J.N., and Vellido, A. Finding Discriminative
Subtypes of Aggressive Brain Tumours using Magnetic Resonance
Spectroscopy. In Procs. of the 32nd Annual International
Conference of the IEEE Engineering in Medicine and Biology
Society (EMBC 2010)
Buenos Aires, Argentina
Vellido,
A., Castro, F., Nebot, A. Clustering Educational Data. In
Romero, C., Ventura, S., Pechenizkiy, M., Baker, R.S.J.d.
(eds.) Handbook of
Educational data Mining, CRC Press, Taylor &
Francis Group, pp.75-92.
Lisboa, P.J.G. Vellido, A. Tagliaferri, R. Napolitano, F. Ceccarelli, M. Martin-Guerrero, J.D. Biganzoli, E. Data Mining in Cancer Research, IEEE Computational Intelligence Magazine, 5(1), 14-18
Ortega-Martorell,
S., Olier, I., Vellido, A., Julià-Sapé, M., Arús, C. Spectral Prototype
Extraction for the discrimination of glioblastomas from
metastases in a SV 1H-MRS brain tumour database. ISMRM-ESMRMB Joint Annual
Meeting.
Lisboa,
P.J.G., Vellido, A., Martín, J.D. Computational Intelligence
in biomedicine: Some contributions. In Procs. of the 18th
European Symposiun on Artificial Neural Networks (ESANN 2010), 429-438.
Olier,
I., Amengual, J., Vellido, A. Segmentation of EMG time series
using a variational Bayesian approach for the robust
estimation of cortical silent periods. In Procs. of the 18th
European Symposiun on Artificial Neural Networks (ESANN 2010), 439-444.
Olier,
I., Vellido, A., Giraldo, J. Kernel Generative Topographic
Mapping. In Procs. of the 18th European Symposiun on
Artificial Neural Networks (ESANN 2010), 481-486.
Ortega-Martorell,
S., Olier, I., Vellido, A., Julià-Sapé, M., Arús, C. Spectral
Prototype Extraction for dimensionality reduction in brain
tumour diagnosis. In Procs. of the 18th European Symposiun
on Artificial Neural Networks (ESANN 2010), 445-450.
Cruz, R., Vellido, A. Semi-Supervised Geodesic Generative Topographic Mapping. Pattern Recognition Letters, 31(3), 202-209.
González-Navarro,
F.F., Belanche-Muñoz, Ll.A., Romero, E., Vellido, A.,
Julià-Sapé, M., Arús, C. Feature and model selection with
discriminatory visualization for diagnostic classification of
brain tumours. Neurocomputing, 73(4-6), 622-632.
2009
Cruz, R., and Vellido,
A., Semi-supervised Outcome Prediction for a Type of
Human Brain Tumour Using Partially Labeled MRS Information. In
Procs. of the Intelligent Data Engineering and
Automated Learning (IDEAL
2009) International Conference, Lecture Notes in
Computer Science, LNCS 5788,
168-175
Olier, I., Vellido, A. Clustering and Visualization of Multivariate Time Series. In Soria-Olivas, E. et al. (eds.) The Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques, Vol.I, ch.8, pp.176-194. Information Science Reference, New York.
Vellido,
A., Romero, E., González-Navarro, F.F., Belanche-Muñoz, Ll.,
Julià-Sapé, M., Arús, C. Outlier exploration and diagnostic
classification of a multi-centre 1H-MRS brain
tumour database. Neurocomputing, 72(13-15), 3085-3097.
Romero, E., Vellido, A., Julià-Sapé, M, and Arús, C. Discriminating glioblastomas from metastases in a SV 1H-MRS brain tumour database. In Proceedings of the 26th Annual Meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB 2009), Antalya, Turkey, p.18.
Arizmendi, A., Vellido, A., Romero, E. Frequency Selection for the Diagnostic Characterization of Human Brain Tumours. In Procs. of the CCIA 2009.
Cruz, R., and Vellido, A. Comparative evaluation of Semi-Supervised Geodesic GTM. In The 4th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2009). LNAI 5573, pp.344-351.
Romero,
E., Vellido, A., and Sopena, J.M. Feature selection with
single-layer perceptrons for a multicentre 1H-MRS
brain tumour database. In The 10th International
Work-Conference on Artificial Neural Networks (IWANN 2009). LNCS 5517, pp.1013–1020.
Vellido, A., and Lisboa, P.J.G. (eds.) Investigating Human Cancer with Computational Intelligence Techniques. In KES Recent Research Results series. Future Technology Press. ISBN: 978-0-9561516-0-5
Vellido,
A. and Lisboa, P.J.G. Preface to Investigating Human Cancer with
Computational Intelligence Techniques. In KES Recent Research Results
series. Future Technology
Press, vii-viii.
Nebot, A., Castro, F., Vellido, A., Julià-Sapé, M., and Arús, C. Rule-based assistance to brain tumour diagnosis using LR-FIR. In Investigating Human Cancer with Computational Intelligence Techniques. KES Recent Research Results series. Future Technology Press, 83-92.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. Exploratory
characterization of a multi-centre 1H-MRS brain
tumour database. In Investigating
Human Cancer with Computational Intelligence Techniques.
KES Recent Research Results series. Future Technology Press,
55-67.
Schleif, F.-M., Biehl, M., and Vellido, A. Advances in machine learning and computational intelligence. Neurocomputing, 72(7-9), 1377-1378.
2008
Olier,
I., Vellido, A. Variational Bayesian Generative Topographic
Mapping. Journal of Mathematical
Modelling and Algorithms, 7(4), 371-387.
Lisboa,
P.J.G., Romero, E., Vellido, A., Julià-Sapé, M., and
Arús, C. Classification, Dimensionality Reduction, and
Maximally Discriminatory Visualization of a Multicentre 1H-MRS
Database of Brain Tumors. In The Seventh International
Conference on Machine Learning and Applications (ICMLA'08), 613-618.
Cruz,
R., Vellido, A. On the Improvement of the Mapping
Trustworthiness and Continuity of a Manifold Learning Model.
In Procs. of the 9th International Conference on
Intelligent Data Engineering and Automated Learning (IDEAL 2008). LNCS 5326,
266-273.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. Exploring
outlierness and its causes in a 1H-MRS brain tumour
database. In Proceedings of e-TUMOUR Workshop ‘Towards Brain
Tumour Classification by Molecular Profiling’, Valencia,
Spain.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. Nonlinear
dimensionality reduction for the exploration of outliers in a
multicentre 1H-MRS database of brain tumours. In
Proceedings of the 25th Annual Meeting of the European Society
for Magnetic Resonance in Medicine and Biology (ESMRMB).
Cruz,
R., Vellido, A. Geodesic Generative Topographic Mapping. In
Proceedings of the 11th Ibero-American Conference on
Artificial Intelligence (IBERAMIA
2008). LNAI
5290, 113-122.
Cruz,
R., Vellido, A. Unfolding the Manifold in Generative
Topographic Mapping. In Proceedings of the 3rd International
Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008). LNAI 5271,
392-399 .
Olier,
I., Vellido, A. Advances in Clustering and Visualization of
Time Series using GTM Through Time. Neural Networks,
21(7), 904-913. preprint
Castro,
F., Vellido, A., Nebot, À., and Minguillón, J. Detección
de Estudiantes con Comportamiento Atípico en Entornos de
Aprendizaje e-Learning. In Llamas-Nistal, M., Vaz de Carvalho,
C., and Rueda Artunduaga, C. (eds.) TICAI2006: TICs para el Aprendizaje de
la Ingeniería, pp.23-30. IEEE, Sociedad de Educación:
Capítulos Español, Portugués y Colombiano.
Nebot, A., Castro, F., Vellido, A., Julià-Sapé, M. and Arús, C. Rule-based assistance to brain tumour diagnosis using LR-FIR. In Procs. of the 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2008). LNAI 5178, Vol. II, 173-180.
Vellido, A., Julià-Sapé, M., Romero, E. and Arús, C. Exploratory characterization of outliers in a multi-centre 1H-MRS brain tumour dataset. In Procs. of the 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2008). LNAI 5178, Vol. II, 189-196.
Vellido,
A., Velazco, J.S. Assessment of the effect of noise on an
unsupervised feature selection method for Generative
Topographic Mapping. In 10th International Conference on
Enterprise Information Systems (ICEIS 2008).
Vellido, A., Velazco, J.S. The effect of noise and sample size on an unsupervised feature selection method for manifold learning. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 523-528.
Olier, I., Vellido, A. On the benefits for model regularization of a Variational formulation of GTM. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 1569-1576.
Olier, I., Vellido, A. A Variational Formulation for GTM Through Time. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 517-522.
Vellido,
A., Biganzoli, E., Lisboa, P.J.G. Machine learning in cancer
research: implications for personalised medicine. In Procs. of the 16th
European Symposiun on Artificial Neural Networks (ESANN 2008), 55-64.
Romero,
E., Julià-Sapé, M., Vellido, A. DSS-oriented exploration of a
multi-centre magnetic resonance spectroscopy brain tumour
dataset through visualization. In Procs. of the 16th
European Symposiun on Artificial Neural Networks (ESANN 2008), 95-100.
Cruz,
R., Vellido, A. Two-Stage Clustering of a Human Brain Tumour
Dataset Using Manifold Learning Models. In Proceedings of the
International Conference on Bio-inspired Systems and Signal
Processing, BIOSIGNALS 2008,
Funchal, Madeira, Portugal. INSTICC Press. pp.191-196.
Vellido, A., Lisboa, P.J.G.
Machine Learning in Human Cancer Research. In Svensson, H.A.
(Ed.): Neurocomputing
Research Developments. Nova Publishers, 163-180.
2007
Olier, I., Vellido, A. Variational GTM. In 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2007), LNCS Vol.4881, 77-86. (pdf)
Cruz, R., Vellido, A. Mining a Human Brain Tumour Dataset for Clinical Decision Support : Advances in the AIDTumour Project. In MICAI 2007, Workshop on Data Mining Applications & Current Trends.
Olier, I., Vellido, A. A Variational Bayesian Formulation for GTM Through Time: Theoretical Foundations. Technical Report LSI-07-38-R.Universitat Politècnica de Catalunya, UPC, Barcelona, Spain. (download)
Olier, I., Vellido, A. A Variational
Bayesian Formulation for GTM: Theoretical Foundations.
Technical Report LSI-07-33-R.Universitat Politècnica de Catalunya,
UPC, Barcelona, Spain. (download)
Cruz,
R., Vellido, A. On the Influence of Class Information in the
Two-Stage Clustering of a Human Brain Tumour Dataset. In
Procs. of the 6th Mexican Conference on Artificial
Intelligence (MICAI 2007).
LNAI 4827, 472-482.
(pdf)
Cruz, R., Vellido, A. On the Initialization of Two-Stage Clustering with class-GTM. In Proceedings of the 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA+TTIA 2007, LNAI Vol.4788, 50-59. (pdf)
Cruz, R., Vellido, A. Evaluation of a Two-Stage Clustering Procedure Using Class Information in Generative Topographic Mapping. In I.Rojas Ruiz and H. Pomares Cintas (eds.) Actas del II Simposio de Inteligencia Computacional (IEEE SICO 2007), Thomson, pp.17-24.
García, D.L. , Vellido, A. and Nebot, A., Finding relevant features for the churn analysis-oriented segmentation of a telecommunications market. In I.Rojas Ruiz and H. Pomares Cintas (eds.) Actas del II Simposio de Inteligencia Computacional (IEEE SICO 2007), Thomson, pp.301-310.
Vellido,
A., Andrade, A.O. Determination of feature relevance for the
grouping of motor unit action potentials through a generative
mixture model. Biomedical Signal Processing and Control,
2(2), 111-121.
Cruz, R., Vellido, A. Limits to the Use of Class Information in a GTM-based Two-Stage Clustering Procedure. In F.J.Ferrer-Troyano et al. (eds.), Actas del IV Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA 2007), Thomson, pp.303-312.
Castro,
F., Vellido, A., Nebot, A., Mugica, F. Applying Data Mining
Techniques to e-Learning Problems. In: Jain, L.C., Tedman,
R.A. and Tedman, D.K. (eds.) Evolution of Teaching and Learning Paradigms in
Intelligent Environment. Studies in Computational
Intelligence, Vol.62, Springer-Verlag, 183-221.
Vellido, A., Castro, F., Etchells, T.A., Nebot, A., and Mugica, F. Data Mining of Virtual Campus Data. In: Jain, L.C., Tedman, R.A and Tedman, D.K (eds.) Evolution of Teaching and Learning Paradigms in Intelligent Environment. Studies in Computational Intelligence, Vol.62, Springer-Verlag, 223-254.
Vellido, A., Lisboa, P.J.G.
Neural networks and other machine learning methods in cancer
research. In Procs. of IWANN
2007.LNCS
Vol. 4507, 964-971. (pdf)
García, D.L. , Vellido, A. and Nebot, A., Identification of churn routes in the Brazilian telecommunications market. In Procs. of the 15th European Symposiun on Artificial Neural Networks, ESANN 2007, 585-590.
Vellido,
A., Martí, E., Comas, J., Rodríguez-Roda, I., and Sabater, F.
Exploring the ecological status of human altered streams
through Generative Topographic Mapping. Environmental
Modelling & Software, 22(7), 1053-1065. (download).
García, D.L. , Vellido, A. and Nebot, A., Predictive Models in Churn Data Mining: A Review. Technical Report LSI-07-4-R, Universitat Politècnica de Catalunya, UPC, Barcelona, Spain. (download)
García, D.L, Vellido, A., and Nebot, A. Customer Continuity Management as a Foundation for Churn Data Mining. Technical Report LSI-07-2-R. Universitat Politècnica de Catalunya, UPC, Barcelona, Spain. (download)
Cruz, R. and Vellido, A., Elements of Generative Manifold Learning for semi-supervised tasks. Technical Report LSI-07-1-R. Universitat Politècnica de Catalunya, UPC, Barcelona, Spain. (download)
2006
Vellido, A., Missing data imputation through GTM as a mixture of t-distributions. Neural Networks, 19(10), 1624-1635. (download)
Cruz, R. and Vellido, A., Clustering of brain tumours through constrained manifold learning using class information. Learning'06 International Conference. 'Between Learning and Data Mining' special session, 3rd of October, Vilanova i la Geltrú, Spain.
Spate, J., Gibert, K., Sànchez-Marrè, M., Frank, E., Comas, J., Athanasiadis, I., and Vellido, A. Data Mining as a Tool for Analysing Environmental Systems. Learning'06 International Conference. 'Between Learning and Data Mining' special session, 3rd of October, Vilanova i la Geltrú, Spain.
Poveda, J. and Vellido, A. Neural Network Models for Language Acquisition: A Brief Survey. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 1346-1357.
Olier, I. and Vellido, A., Time Series Relevance Determination through a topology-constrained Hidden Markov Model. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 40-47. (download)
Vellido, A. , Etchells, T.A. , García, D.L. and Nebot, À., Describing customer loyalty to Spanish petrol stations through rule extraction. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 970-977.
Vellido, A., Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping. 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece. LNCS Vol.4132, 361-370. (download)
Cruz, R. and Vellido, A., On the improvement of brain tumour data clustering using class information, In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.
Olier, I. and Vellido, A., Capturing the Dynamics of Multivariate Time Series Through Visualization Using Generative Topographic Mapping Through Time, In proceedings of the 1st IEEE International Conference on Engineering of Intelligent Systems, IEEE ICEIS'2006, Islamabad, Pakistán, pp.492-497. (download)
Etchells,T.A., Nebot, A., Vellido, A., Lisboa, P.J.G., and Múgica, F., Learning what is important: feature selection and rule extraction in a virtual course. In Proceedings of the 14th European Symposium on Artificial Neural Networks, ESANN 2006, Bruges, Belgium, 401-406.
Etchells, T.A., Vellido, A., Martí, E., Lisboa, P.J.G., and Comas, J., On the prediction of the ecological status of human-altered streams and its rule-based interpretation. 3rd Biennial meeting of the International Environmental Modelling and Software Society, iEMSs'2006. Data Mining Workshop.
Vellido, A., Comas, J., Cruz, R., and Martí, E., Finding relevant features for the characterization of the ecological status of human altered streams using a constrained mixture model. 3rd Biennial meeting of the International Environmental Modelling and Software Society, iEMSs'2006. Data Mining Workshop.
Vellido, A., Lisboa, P.J.G., and Vicente, D. Robust analysis of MRS brain tumour data using t-GTM. Neurocomputing, 69(7-9), 754-768. (pdf)
Andrade, A., and Vellido, A., (2006) Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping, In Proc. of the 25th IASTED International ConferenceModelling, Identification, and Control (MIC'06), Feb.6-8, Lanzarote, Canary Islands, Spain, pp.507-512. (pdf)
Vellido, A. and Lisboa, P.J.G., Handling outliers in brain tumour MRS data analysis through robust topographic mapping, Computers in Biology and Medicine, 36(10), 1049-1063. (download)
Vellido, A., Castro, F., Nebot, A., and Múgica, F., (2006) Characterization of atypical virtual campus usage behavior through robust generative relevance analysis, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.183-188.
Nebot, A., Castro, F., Múgica, F., and Vellido, A., (2006) Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79. [Shortlisted for The Fifth International Competition of Ph.D. Students in the WBE Area]
2005
(2005) Capturing the dynamics of multivariate time series through visualization using Generative Topographic Mapping Through Time. Technical Report LSI-05-52-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
,Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Detecting atypical student behaviour on an e-learning system. VI Congreso Nacional de Informática Educativa; I Simposio Nacional de Tecnologías de la Información y las Comunicaciones en la Educación, SINTICE’2005, Granada, Spain, September 2005, 153-160.
Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Finding relevant features to characterize student behavior on an e-learning system. In: International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS 2005), Las Vegas, Nevada, USA, June 2005.
(2005) Comparative assessment of the robustness of missing data imputation through Generative Topographic Mapping, In Cabestany, J., Prieto, A., and Sandoval, F. (Eds.) Proc. of the IWANN 2005, Vilanova i la Geltru, Barcelona, Spain. LNCS Vol.3512, 771-778.
,Vellido, A. (2005) Preliminary theoretical results on a feature relevance determination method for Generative Topographic Mapping. Technical Report LSI-05-13-R, Universitat Politècnica de Catalunya, UPC, Barcelona, Spain.
Vellido, A., Lisboa, P.J.G., and Vicente,D. (2005) Handling outliers and missing data in brain tumor clinical assessment usign t-GTM. In Proc. of the European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, 121-126.
Vellido,
A. and Lisboa, P.J.G. (2005) Functional topographic mapping
for robust handling of outliers in brain tumour data. In
Proc. of the European Symposium on Artificial Neural
Networks, ESANN 2005, Bruges, Belgium, 133-138.
2004
(2005) Capturing the dynamics of multivariate time series through visualization using Generative Topographic Mapping Through Time. Technical Report LSI-05-52-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
,Olier, I., and Vellido,
A. (2004) Assessing the robustness of missing data imputation
through Generative Topographic Mapping. ACIA Newsletter, 31,
14-20.
Vicente, D. and Vellido,
A. (2004) Review of Hierarchical Models for Data Clustering
and Visualization. In R.Giráldez, J.C. Riquelme, J.S.
Aguilar-Ruiz (Eds.) Tendencias de la Minería de Datos en
España. Red Española de Minería de Datos.
Alquézar, R., Belanche,
L., Nebot, A., Romero, E., and Vellido, A. (2004)
Investigación actual del grupo SOCO: Metodologías híbridas de
Soft Computing. In R.Giráldez, J.C. Riquelme, J.S.
Aguilar-Ruiz (Eds.) Tendencias de la Minería de Datos en
España. Red Española de Minería de Datos.
Vellido, A. (2004)
Missing data imputation through Generative Topographic Mapping
as a mixture of t-distributions: Theoretical developments.
Technical Report LSI-04-50-R, Universitat Politècnica de
Catalunya (UPC), Barcelona, Spain.
Vellido, A. (2004)
Generative Topographic Mapping as a constrained mixture of
Student t-distributions: Theoretical developments. Technical
Report LSI-04-44-R, Universitat Politècnica de Catalunya
(UPC), Barcelona, Spain.
Vicente, D., Vellido,
A., Martí, E., Comas, J., and Rodriguez-Roda, I. (2004),
“Exploration of the ecological status of Mediterranean rivers:
Clustering, visualizing and reconstructing streams data using
Generative Topographic Mapping”. In W.I.T. Transactions on
Information and Communication Technologies, Vol.33, 121-130.
Vellido, A., Olier, I.,
Martí, E., Comas, J., and Rodríguez-Roda, I. (2004) STREAMES
project: Exploration of the ecological status of Mediterranean
rivers using Generative Topographic Mapping. Poster
presentation at BESAI 2004 - 4th ECAI Workshop on Binding
Environmental Sciences and Artificial Intelligence. August
2004, Valencia, Spain.
Vellido, A., El-Deredy,
W., and Lisboa, P.J.G. (2004) Studying embedded human EEG
dynamics using Generative Topographic Mapping . Technical
Report LSI-04-8-R, Universitat Politècnica de Catalunya (UPC),
Barcelona, Spain.
Vellido,
A., and El-Deredy, W. (2004) Exploring dopamine-mediated
reward processing through the analysis of EEG-measured
gamma-band brain oscillations. Technical Report LSI-04-7-R,
Universitat Politècnica de Catalunya (UPC), Barcelona,
Spain.
2003
Vellido, A., El-Deredy, W., and Lisboa, P.J.G. (2003) Selective Smoothing of the Generative Topographic Mapping. IEEE Transactions on Neural Networks, 14(4), 847-852.
Vellido, A., El-Deredy, W., Gruber, T., Zald, D.H., McGlone, F.P., and Müller, M.M. (2003) Reward predictability and oscillatory brain processes. In The Annual Computational Neuroscience Meeting (CNS'2003). Poster presentation. Alicante, Spain.
2002
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2002) Characterizing and Segmenting the On-Line Customer Market Using Neural Networks. In E-Commerce and Intelligent Methods. Heidelberg: Springer-Verlag, 101-119.
Vellido, A. (2002) Neural networks for B2C e-commerce analysis: some elements of best practice. In Proceedings of the 4th International Conference On Enterprise Information Systems (ICEIS 2002) Ciudad Real, Spain.
2001
Vellido, A and Lisboa, P.J.G (2001) An electronic commerce application of the Bayesian Framework for MLPs: the Effect of Marginalization and ARD. Neural Computing & Applications. 10(1), 3-11.
2000
Lisboa, P.J.G., Vellido, A. and Edisbury, B. (Editors, 2000) Business Applications of Neural Networks. Singapore: World Scientific.
Lisboa, P.J.G., Vellido, A. (2000) Preface: Business Applications of Neural Networks. In Business Applications of Neural Networks. Singapore: World Scientific.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) Characterizing and segmenting the business-to-consumer e-commerce market using neural networks. In Business Applications of Neural Networks. Singapore: World Scientific.
Lisboa, P.J.G., Vellido, A. and Wong, H.
(2000) Outstanding
Issues
for Clinical Decision Support with Neural Networks. In Artificial
Neural
Networks in Medicine and Biology. Springer, London, 63-71.
Vellido, A., Lisboa, P.J.G. and Meehan, K.
(2000) The
Generative
Topographic Mapping as a principled model for data
visualization and market segmentation: an electronic commerce
case study. International Journal of Computers,
Systems, and Signals. 1(2), 119-138.
Vellido, A, Lisboa, P.J.G and Meehan, K.
(2000) Quantitative characterization and prediction of on-line
purchasing behaviour: a latent variable approach.
International Journal of Electronic Commerce, 4(4),
83-104.
Lisboa. P.J.G., Vellido, A. and Wong, H.
(2000) Bias
reduction
in skewed binary classification with Bayesian neural networks.
Neural Networks. 13, 407-410.
Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) Segmenting the e-commerce market using the Generative Topographic Mapping. In Proceedings of the MICAI-2000, 470-481. Acapulco, México.
Vellido, A., Lisboa, P.J.G. & Meehan,
K. (2000) A
systematic quantitative methodology for characterizing the
business-to-consumer e-commerce market. ACM SIGBIO
Newsletter, Vol.20(1), p.24.
1999
Vellido, A., Lisboa, P.J.G and Vaughan, J. (1999) Neural networks in business: a survey of applications (1992-1998) Expert Systems with Applications. 17, 51-70.
Vellido, A., Lisboa, P.J.G and Meehan, K.
(1999) Segmentation
of
the on-line shopping market using neural networks. Expert
Systems
with Applications. 17, 303-314.
1998
Lisboa, P.J.G., Kirby, S.J.P., Vellido, A., Lee, Y.Y.B. and El-Deredy, W. (1998) Assessment of Statistical and Neural Network Methods in NMR Spectral Classification and Metabolite Selection. Nuclear Magnetic Resonance in Biomedicine. 11, 225-234.
Lisboa, P.J.G., Wong, H., Vellido, A., Kirby, S.P.J., Harris, P. and Swindell, R. (1998) Survival of Breast Cancer Patients Following Surgery: a Detailed Assessment of the Multi-Layer Perceptron and Cox’s Proportional Hazard Model. In Proceedings of the World Congress on Computational Intelligence, IJCNN'1998, 112-116. Anchorage, Alaska, USA.
Lisboa, P.J.G., Vellido, A., Aung, H., El-Deredy, W., Lee, Y.Y.B. and Kirby, S.P.J. (1998) Quantification of uncertainty in tissue characterisation with NMR Spectra. In Proceedings of the 6th Scientific Meeting of the International Society for Magnetic Resonance in Medicine, Abstract 1851, Sidney, Australia.
Y. Lee,A. Vellido,W. El-Deredy,S. Kirby,P.
Lisboa (1998) Neural
networks
in practice-an example from magnetic resonance
spectroscopy. In Proc. of the IEE Colloquium on
Intelligent Methods in Healthcare and Medical Applications
(Digest No. 1998/514)
1997
Lisboa, P.J.G., El-Deredy, W., Vellido, A., Etchells, T. and Pountney, D.C. (1997) Automatic Variable Selection and Rule Extraction Using Neural Networks. In Proceedings of the 15th IMACS World Congress on Scientific Computation, Modelling and Applied Mathematics, 461-466, Berlin, Germany
Lisboa, P.J.G, Branston, N.M., El-Deredy, W. and Vellido, A. (1997) Tissue Characterisation with NMR Spectroscopy; Current State and Future Prospects for the Application of Neural Networks Analysis. In Proceedings of the IEEE/INNS International Joint Conference on Neural Networks, IJCNN'1997, 1385-1390, Houston, USA, pp.1385-1390.
Lisboa, P.J.G., Vellido, A., El-Deredy, W. and Auer, D. (1997) Pattern Recognition Analysis of MRS:A Benchmark of Linear Statistical Methods and Neural Networks. In Proceedings of the 14th Annual Meeting of the European Society of Magnetic Resonance in Medicine and Biology, Abstract 224, Brussels, Belgium.
P. Lisboa,S. Kirby,A. Vellido,B. Lee (1997) Pattern recognition methods for MRS analysis and classification. In Proc. of the IEE Colloquium on Realising the Clinical Potential of Magnetic Resonance Spectroscopy: The Role of Pattern Recognition (Digest No: 1997/082)
Books and chapters in books
Biganzoli, E., Vellido, A.,
Ambrogi, F., Tagliaferri, R. (Editors) Computational
Intelligence Methods for Bioinformatics and
Biostatistics, LNBI/LNCS
7548, 2012.
Ribas,
V.J., Ruiz-Rodríguez, J.C., and Vellido, A.
(2012) Intelligent management of sepsis in the intensive care
unit. In: R. Magdalena-Benedito, E. Soria, J. Guerrero
Martínez, J. Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.1-16, doi:10.4018/978-1-4666-1803-9.ch001
Arizmendi,
C.J.,
Vellido,
A.,
Romero, (2012) E. Preprocessing MRS Information for
Classification of Human Brain Tumours. In: R.
Magdalena-Benedito, E. Soria, J. Guerrero Martínez, J.
Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.29-49, doi: 10.4018/978-1-4666-1803-9.ch003
Cárdenas,
M.I.,
Vellido,
A.,
Olier, I., Rovira, X., Giraldo, J. (2012) Kernel Generative
Topographic Mapping of Protein Sequences. In: R.
Magdalena-Benedito, E. Soria, J. Guerrero Martínez, J.
Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.194-207, doi: 10.4018/978-1-4666-1803-9.ch013
Vellido,
A., Castro, F., Nebot, A. (2010) Clustering Educational Data.
In Romero, C., Ventura, S., Pechenizkiy, M., Baker, R.S.J.d.
(eds.) Handbook of
Educational data Mining, CRC Press, Taylor &
Francis Group, pp.75-92.
Olier,
I., Vellido, A. (2009) Clustering and Visualization of
Multivariate Time Series. In Soria-Olivas, E. et al. (eds.) The Handbook of Research on
Machine Learning Applications and Trends: Algorithms,
Methods, and Techniques, Vol.I, ch.8, pp.176-194.
Information Science Reference, New York.
Vellido, A., and Lisboa, P.J.G. (eds.) Investigating Human Cancer with Computational Intelligence Techniques. In KES Recent Research Results series. Future Technology Press. 2009. ISBN: 978-0-9561516-0-5
Vellido,
A. and Lisboa, P.J.G. (2009) Preface to Investigating Human Cancer with
Computational Intelligence Techniques. In KES Recent Research Results
series. Future Technology
Press, vii-viii.
Nebot, A., Castro, F., Vellido, A., Julià-Sapé, M., and Arús, C. (2009) Rule-based assistance to brain tumour diagnosis using LR-FIR. In Investigating Human Cancer with Computational Intelligence Techniques. KES Recent Research Results series. Future Technology Press, 83-92.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. (2009)
Exploratory characterization of a multi-centre 1H-MRS
brain tumour database. In Investigating
Human Cancer with Computational Intelligence Techniques.
KES Recent Research Results series. Future Technology Press,
55-67.
Castro, F., Vellido,
A., Nebot, À., and Minguillón, J. (2008) Detección de
Estudiantes con Comportamiento Atípico en Entornos de
Aprendizaje e-Learning. In Llamas-Nistal, M., Vaz de Carvalho,
C., and Rueda Artunduaga, C. (eds.) TICAI2006: TICs para el Aprendizaje de
la Ingeniería, pp.23-30. IEEE, Sociedad de Educación:
Capítulos Español, Portugués y Colombiano.
Vellido, A., Lisboa, P.J.G. (2008) Machine Learning in Human Cancer Research. In Svensson, H.A. (Ed.): Neurocomputing Research Developments. Nova Publishers, 163-180.
Castro, F., Vellido, A., Nebot, A., Mugica, F. (2007) Applying Data Mining Techniques to e-Learning Problems. In: Jain, L.C., Tedman, R. and Tedman, D. (eds.) Evolution of Teaching and Learning Paradigms in Intelligent Environment. Studies in Computational Intelligence, Vol.62, Springer-Verlag, 183-221.
Vellido, A., Castro, F., Etchells, T.A., Nebot, A., and Mugica, F. (2007) Data Mining of Virtual Campus Data. In: Jain, L.C., Tedman, R. and Tedman, D. (eds.) Evolution of Teaching and Learning Paradigms in Intelligent Environment. Studies in Computational Intelligence, Vol.62, Springer-Verlag, 223-254.
Vicente, D. and Vellido, A. (2004) Review of Hierarchical Models for Data Clustering and Visualization. In R.Giráldez, J.C. Riquelme, J.S. Aguilar-Ruiz (Eds.) Tendencias de la Minería de Datos en España. Red Española de Minería de Datos.
Alquézar, R., Belanche, L., Nebot, A., Romero, E., and Vellido, A. (2004) Investigación actual del grupo SOCO: Metodologías híbridas de Soft Computing. In R.Giráldez, J.C. Riquelme, J.S. Aguilar-Ruiz (Eds.) Tendencias de la Minería de Datos en España. Red Española de Minería de Datos.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2002) Characterizing and Segmenting the On-Line Customer Market Using Neural Networks. In E-Commerce and Intelligent Methods. Heidelberg: Springer-Verlag, 101-119
Lisboa, P.J.G., Vellido, A. and Edisbury, B. (Editors, 2000) Business Applications of Neural Networks. Singapore: World Scientific.
Lisboa, P.J.G., Vellido, A. (2000) Preface: Business Applications of Neural Networks. In Business Applications of Neural Networks. Singapore: World Scientific.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) Characterizing and segmenting the business-to-consumer e-commerce market using neural networks. In Business Applications of Neural Networks. Singapore: World Scientific.
Lisboa, P.J.G., Vellido, A. and Wong, H. (2000) Outstanding Issues for Clinical Decision Support with Neural Networks. In Artificial Neural Networks in Medicine and Biology. Springer, London, 63-71
Journals
Vellido, A. (2019) The importance of interpretability
and visualization in Machine Learning for applications
in medicine and health care. Neural Computing
& Applications, accepted. draft.
Aushev, A., Ribas Ripoll, V.,
Vellido, A., Aletti, F., Bollen Pinto, B.,
Bendjelid, K., Herpain, A., Hendrik Post, E.
Romay Medina, E., Ferrer, R., Baselli, G.
(2018) Feature selection for the accurate
prediction of septic and cardiogenic shock ICU
mortality in the acute phase. PLoS ONE,
13(11): e0199089.
https://doi.org/10.1371/journal.pone.0199089.
Ribas Ripoll, V., Vellido, A. (2018) Blood pressure assessment with differential pulse transit time and deep learning: a proof of concept. Kidney Diseases; DOI: 10.1159/000493478
Hueso
M, Vellido A (2018)
Artificial
Intelligence and Dialysis.
Kidney Diseases;
DOI:
10.1159/000493933
Vellido A (2018) Societal Issues Concerning the Application of Artificial Intelligence in Medicine. Kidney Diseases, in press, available online, free access https://doi.org/10.1159/000492428.
König,
C., Shaim, I. , Vellido, A., Romero, E., Alquézar, R.,
Giraldo, J. (2018) Using
machine learning tools for protein database
biocuration assistance, Scientific Reports,
8:10148.
Hueso M, Vellido A, Montero N, Barbieri C, Ramos R, Angoso M, Cruzado JM, Jonsson A (2018) Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy. Kidney Diseases; 4:1-9. open access.
Vellido
A, Ribas V, Subirats L, Morales C, Ruiz Sanmartín A,
Ruiz Rodríguez JC (2018) Machine
Learning for Critical Care: State-of-the-Art and a
Sepsis Case Study, BioMedical Engineering
OnLine, 17(S1):135.
König C, Alquézar R, Vellido A,
Giraldo J (2018) Systematic analysis of primary sequence
domain segments for the discrimination between class C
GPCR subtypes, Interdisciplinary Sciences:
Computational Life Sciences, 10(1), 43-52.
A.
Shkurin, A. Vellido (2017) Using random forests for
assistance in the curation of G-protein coupled receptor
databases. BioMedical Engineering OnLine,
16(Suppl 1):75
D.L.
García, À. Nebot, A. Vellido (2017)
Intelligent data analysis approaches to churn as a
business problem: a survey. Knowledge and
Information Systems,
51(3):719-774.
DOI: 10.1007/s10115-016-0995-z (draft)
X. Cipriano, A. Vellido, J. Cipriano, J. Martí, S. Danov (2017) Application of clustering and simulation methods for the analysis of socio-economical and technical factors influencing the energy refurbishment of neighbourhoods. Energy Efficiency, 10(2), 359-382. doi: 10.1007/s12053-016-9460-9
C.L.
König, M.I. Cárdenas, J. Giraldo, R. Alquezar, A.
Vellido (2015) Label noise in subtype discrimination of
class C G-protein coupled receptors: A systematic
approach to the analysis of classification errors. BMC
Bioinformatics, 16(1):314. open
access
P.J.G. Lisboa,
J.D. Martín,
and A. Vellido
(2015) Making Nonlinear Manifold Learning Models
Interpretable: the Manifold Grand Tour. Expert
Systems with Applications, 42(22),
8982-8988.
M.I.
Cárdenas, A. Vellido, C.
König, R. Alquézar and J.
Giraldo (2015) Visual
Characterization of
Misclassified Class C
GPCRs through
Manifold-based Machine
Learning Methods. Genomics
and Computational
Biology,
Accepted
R.
Cruz-Barbosa, A. Vellido, J. Giraldo (2015) The
influence of alignment-free sequence
representations on the
semi-supervised classication of
Class C G
Protein-Coupled Receptors. Medical
& Biological Engineering
& Computing, 53(2), 137-149,
available
online
from Nov 2014.
C.
König, R. Alquézar, A. Vellido and J. Giraldo
(2014) Finding class C GPCR
subtype-discriminating n-grams through feature
selection. Journal of Integrative
Bioinformatics, 11(3):254.
doi: 10.2390/biecoll-jib-2014-254..
V. Ribas, A. Vellido, E. Romero and J.C. Ruiz-Rodríguez (2014) Sepsis Mortality Prediction with Quotient Basis Kernels. Artificial Intelligence in Medicine, 61(1), 45-52. DOI:10.1016/j.artmed.2014.03.004
C.
Arizmendi, D.A. Sierra, A. Vellido and E.Romero (2014)
Automated classification of brain tumours from short
echo time in vivo MRS data
using Gaussian decomposition
and Bayesian Neural Networks, Expert Systems with
Applications, 41(11), 5296-5307. doi:
http://dx.doi.org/10.1016/j.eswa.2014.02.031.
Ortega-Martorell,
S., Ruiz, H.,
Vellido, A.,
Olier, I., Romero,
E., Julià-Sapé,
M., Martín, J.D.
,
Jarman, I.H.,
Arús,
C., Lisboa, P.J.G.
(2013)
A novel
semi-supervised
methodology for
extracting tumor
type-specific
MRS sources in
human brain data,
PLoS ONE,
8(12): e83773.
Vilamala,
A., Lisboa, P.J.G., Ortega-Martorell,
S., Vellido, A.
(2013) Discriminant
Convex Non-negative Matrix Factorization
for the Classification of Human Brain
Tumours, Pattern Recognition
Letters, 34(14), 1734–1747.
Cruz-Barbosa, R. and Vellido, A. (2013) Generative manifold learning for the exploration of partially labeled data. Computación & Sistemas, 17(4), 641-653. doi: 10.13053/CyS-17-4-2013-014
Vellido, A., García, D.,
Nebot, À. (2013) Cartogram
Visualization for Nonlinear
Manifold Learning Models. Data
Mining and Knowledge Discovery, 27(1):22-54,
doi: 10.1007/s10618-012-0294-6
Ortega-Martorell, S., Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. (2012) Convex Non-Negative Matrix Factorization for Brain Tumor Delimitation from MRSI Data, PLoS ONE, 7(10):e47824.
Ortega-Martorell, S., Lisboa, P.J.G., Vellido, A.,Julià-Sapé, M., Arús, C. (2012) Non-negative Matrix Factorisation methods for the spectral decomposition of MRS data from human brain tumours. BMC Bioinformatics, 13:38. (draft)
Vellido, A., Romero, E., Julià-Sapé, M., Majós, C.,
Moreno-Torres, À., and Arús, C. (2012) Robust discrimination
of glioblastomas from metastatic brain tumors on the basis of
single-voxel proton MRS. NMR in Biomedicine.
25(6):819–828.
Ribas, V.J., Vellido, A.,
Ruiz-Rodríguez, J.C., Rello, J. (2012) Severe sepsis mortality
prediction with logistic regression over latent factors. Expert
Systems
with Applications, 39(2), 1937-1943.
Arizmendi,
C.,
Vellido, A., Romero, E. (2012) Classification of human brain tumours
from MRS data using discrete wavelet transform and Bayesian
neural networks. Expert Systems with Applications, 39(5),
5223-5232.
Olier, I., Amengual, J. and Vellido, A.
(2011) A variational Bayesian
approach for the robust estimation of cortical silent periods
from EMG time series of brain stroke patients. Neurocomputing,
74(9): 1301-1314.
Cruz, R., Vellido, A., (2011)
Semi-supervised analysis of human brain tumours from partially
labeled MRS information, using manifold learning models. International Journal of Neural
Systems. 21(1): 17-29.
Lisboa,
P.J.G.
Vellido, A. Tagliaferri, R. Napolitano, F.
Ceccarelli, M. Martin-Guerrero, J.D. Biganzoli, E.
(2010) Data Mining in Cancer Research, IEEE
Computational Intelligence Magazine,
5(1), 14-18
Cruz, R., Vellido, A. (2010) Semi-Supervised Geodesic Generative Topographic Mapping. Pattern Recognition Letters, 31(3), 202-209.
González-Navarro,
F.F., Belanche-Muñoz, Ll.A., Romero, E., Vellido, A.,
Julià-Sapé, M., Arús, C. (2010) Feature and model selection
with discriminatory visualization for diagnostic
classification of brain tumours. Neurocomputing, 73(4-6), 622-632.
Vellido,
A.,
Romero, E., González-Navarro, F.F., Belanche-Muñoz, Ll.,
Julià-Sapé, M., Arús, C. (2009) Outlier exploration and
diagnostic classification of a multi-centre 1H-MRS
brain tumour database. Neurocomputing, 72(13-15), 3085-3097.
Schleif, F.-M., Biehl, M., and Vellido,
A. (2009) Advances in machine learning and computational
intelligence. Neurocomputing, 72(7-9), 1377-1378.
Olier,
I., Vellido, A. (2008) Variational Bayesian Generative
Topographic Mapping. Journal of Mathematical
Modelling and Algorithms, 7(4), 371-387.
Olier, I., Vellido, A. (2008) Advances in Clustering and Visualization of Time Series using GTM Through Time. Neural Networks, 21(7), 904-913. preprint.
Vellido, A., Andrade, A.O. (2007)
Determination of feature relevance for the grouping of motor
unit action potentials through a generative mixture model. Biomedical
Signal Processing and Control, 2(2), 111-121.
Vellido, A., Martí,
E., Comas, J., Rodríguez-Roda, I., and Sabater, F. (2007)
Exploring the ecological status of human altered streams
through Generative Topographic Mapping. Environmental
Modelling & Software, 22(7), 1053-1065. (download).
Vellido, A., (2006) Missing data imputation through GTM as a mixture of t-distributions. Neural Networks, 19(10), 1624-1635. (download)
Vellido, A., Lisboa, P.J.G., and Vicente, D. (2006) Robust analysis of MRS brain tumour data using t-GTM. Neurocomputing, 69(7-9), 754-768. (pdf)
Vellido, A. and Lisboa, P.J.G. (2006) Handling outliers in brain tumour MRS data analysis through robust topographic mapping, Computers in Biology and Medicine, 36(10), 1049-1063. (download)
Vellido, A., El-Deredy, W., and Lisboa, P.J.G. (2003) Selective Smoothing of the Generative Topographic Mapping. IEEE Transactions on Neural Networks, 14(4), 847-852
Vellido, A and Lisboa, P.J.G. (2001) An electronic commerce application of the Bayesian Framework for MLPs: the Effect of Marginalization and ARD. Neural Computing & Applications. 10(1)
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) The Generative Topographic Mapping as a principled model for data visualization and market segmentation: an electronic commerce case study. International Journal of Computers, Systems, and Signals. 1(2), 119-138.
Vellido, A, Lisboa, P.J.G and Meehan, K.
(2000) Quantitative characterization and prediction of on-line
purchasing behaviour: a latent variable approach.
International Journal of Electronic Commerce, 4(4),
83-104.
Lisboa. P.J.G., Vellido, A. and Wong, H.
(2000) Bias
reduction
in skewed binary classification with Bayesian neural networks.
Neural Networks. 13, 407-410.
Vellido, A., Lisboa, P.J.G and Vaughan, J.
(1999) Neural
networks
in business: a survey of applications (1992-1998) Expert
Systems
with Applications. 17, 51-70.
Vellido, A., Lisboa, P.J.G and Meehan, K.
(1999) Segmentation
of
the on-line shopping market using neural networks. Expert
Systems
with Applications. 17, 303-314.
Lisboa, P.J.G., Kirby, S.J.P., Vellido, A., Lee, Y.Y.B. and El-Deredy, W. (1998) Assessment of Statistical and Neural Network Methods in NMR Spectral Classification and Metabolite Selection. Nuclear Magnetic Resonance in Biomedicine. 11, 225-234.
Conferences, technical
reports and newsletters
Bilal, A., Vellido, A., Ribas, V. (2018) Enabling interpretation of the outcome of a human obesity prediction machine learning analysis from genomic data. In procs. of the 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics (CIBB 2018) Lisbon, Portugal.
Bacciu,
D., Lisboa, P.J., Martín, J.D., Stoean, R. and Vellido,
A. (2018) Bioinformatics
and medicine in the era of Deep Learning. In
Proceedings of the 26th European Symposium on Artificial
Neural Networks, Computational Intelligence and Machine
Learning (ESANN 2018), Bruges, Belgium,
pp.345-354.
Bilal,
A., Vellido, A., Ribas, V. (2018) Big data analytics for
obesity prediction. In 21st International
Conference of the Catalan Association for Artificial
Intelligence (CCIA
2017) Roses,
Spain. Accepted.
Y.
Hernández–Villegas, V. Mocioiu, D. Ulinic, S.P.
Kyathanahally, A. Vellido, C. Arús, M. Julià-Sapé (2017)
Automated quality control of magnetic resonance spectra
of brain tumors by Convex Non-negative Matrix
Factorization. In 34th Annual Scientific Meeting of the
European Society for Magnetic Resonance in Medicine and
Biology (ESMRMB), Barcelona, Spain.
C. König, R. Alquézar, A. Vellido, J. Giraldo (2017) Discovering subtype specific n-gram motifs in class C GPCR N-termini. In Recent Advances in Artificial Intelligence Research and Development: Proceedings of the 20th International Conference of the Catalan Association for Artificial Intelligence, Deltebre, Terres de L'Ebre, Spain, October 25-27, 2017 (Vol. 300, p. 116). IOS Press
A. Vellido, D.L. García (2017)
Electricity rate planning for the current consumer
market scenario through segmentation of consumption
time series. In Artificial Intelligence in Power and
Energy Systems (AIPES)
18th EPIA Conference on Artificial Intelligence, Porto,
Portugal, LNCS 10423, pp. 295-306, Springer
C. König, R.
Alquézar, A. Vellido, J. Giraldo (2017) Topological
sequence segments discriminate between class C GPCR
subtypes. In 11th
International Conference on Practical Applications of
Computational Biology & Bioinformatics (PACBB 2017),
Porto, Portugal. Accepted
A. Vellido, V. Ribas, C. Morales, A. Ruiz Sanmartín, J.C. Ruiz-Rodríguez (2017) Machine Learning for Critical Care: An Overview and a Sepsis Case Study. In I. Rojas and F. Ortuño (Eds.): Procs. of the 5th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2017), Granada, Spain. Part I, LNBI 10208, pp.15-30, Springer. doi: 10.1007/978-3-319-56148-6_2.
C.
Morales, A. Vellido, V. Ribas (2016) Applying
Conditional Independence Maps to improve
Sepsis Prognosis. Data Mining in Biomedical
Informatics and Healthcare (DMBIH) Workshop.
IEEE International Conference on Data Mining (ICDM
2016), accepted.
J.R.G.
Cárdenas, À. Nebot, F. Mugica, A. Vellido (2016) A
decision making support tool: The Resilience Management
Fuzzy Controller, In 2016 IEEE
Congress on Evolutionary
Computation (CEC / WCCI'16),
pp.2313-2320.
I. Paz, À. Nebot, E. Romero, F. Mugica and A. Vellido (2016) A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration, In 2016 IEEE Congress on Evolutionary Computation (CEC / WCCI'16), pp.1317-1323.
E. Racec, S. Budulan, and A. Vellido (2016) Computational Intelligence in architectural and interior design: a state-of-the-art and outlook on the field. In Artificial Intelligence Research and Development: Proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2016), Barcelona, Spain, Vol. 288, p.108. IOS Press. [draft]
M.I. Cárdenas, A. Vellido and J. Giraldo (2016) Visual exploratory assessment of class C GPCR extracellular domains discrimination capabilities, In Procs. of the 10th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB'16) Advances in Intelligent Systems and Computing series, Vol.477, Springer, pp.31-39.
J.D.
Martín-Guerrero, J.P.G. Lisboa, A. Vellido
(2016) Physics and Machine Learning: Emerging
Paradigms. In Proceedings of the
24th European Symposium on
Artificial Neural Networks,
Computational Intelligence and
Machine Learning (ESANN 2016),
Bruges, Belgium,
pp.319-326. [draft]
V. Mocioiu, N.M.
Pedrosa de Barros, S. Ortega-Martorell,J. Slotboom, U.
Knecht, C. Arús, A. Vellido and M. Julià-Sapé (2016) A
machine learning pipeline for supporting differentiation
of glioblastomas from single brain metastases, In
Proceedings of the 24th European Symposium
on Artificial Neural Networks,
Computational Intelligence and Machine
Learning (ESANN 2016),
Bruges, Belgium.
pp.247-252.
A.
Vilamala, A. Vellido, L. Belanche (2016)
Bayesian Semi Non-negative Matrix Factorisation. In
Proceedings of the 24th European Symposium on Artificial
Neural Networks, Computational Intelligence and Machine
Learning (ESANN 2016), Bruges, Belgium. pp.195-200.
V.
Mocioiu, S.P. Kyathanahally, C. Arús, A. Vellido, M.
Julià-Sapé, Automated quality control for proton
magnetic resonance spectroscopy data using convex
non-negative matrix factorization, In Bioinformatics
and Biomedical Engineering (F. Ortuño, I.Rojas,
eds.) Proceedings of the 4th International Conference, IWBBIO
2016, Granada, Spain, April 20-22, 2016, LNCS/LNBI
9656, pp 719-727
A.
Shkurin and A. Vellido, Random Forests for quality
control in G-Protein Coupled Receptor databases, In Bioinformatics
and Biomedical Engineering (F. Ortuño, I.Rojas,
eds.) Proceedings of the 4th International Conference, IWBBIO
2016, Granada, Spain, April 20-22, 2016, LNCS/LNBI
9656, pp 707-718.
C König, R Alquézar, A Vellido, J Giraldo (2015) The Extracellular N-terminal Domain Suffices to Discriminate Class C G Protein-Coupled Receptor Subtypes from n-Grams of their Sequences, In: Procs. of the International Joint-Conference on Artificial Neural Networks (IJCNN 2015), Killarney, Ireland, pp.2330-2336.
A. Vellido, C. Halka, À. Nebot (2015) A Weighted Cramer's V Index for the Assessment of Stability in the Fuzzy Clustering of Class C G Protein-Coupled Receptors. In F. Ortuño and I. Rojas (Eds.): IWBBIO 2015, Part I, LNCS 9043, pp. 536--547, Springer
A. Tosi, A. Vellido (2014) Probabilistic Geometries as a tool for Interpretability in Dimensionality Reduction Models, In the 8th WiML Workshop, Advances in Neural Information Processing Systems (NIPS 2014), Montreal, Canada.
A.
Tosi, S. Hauberg, A. Vellido, N. Lawrence (2014) Metrics
for probabilistic geometries, In Nevin L. Zhang,
Jin Tian (eds.) Proceedings of The 30th Conference on
Uncertainty in
Artificial Intelligence (UAI
2014),
AUAI Press Corvallis, Oregon, USA, pp.800-808.
M.I. Cárdenas, A. Vellido, J. Giraldo (2014) Exploratory visualization of Metabotropic Glutamate Receptor subgroups through manifold learning. 17th International Conference of the Catalan Association of Artificial Intelligence (CCIA 2014) In L. Museros et al. (Eds.) Artificial Intelligence Research and Development, IOS Press, pp.269-272.
A. Vilamala, Ll. Belanche, A. Vellido (2014) A MAP approach for Convex Non-negative Matrix Factorization in the Diagnosis of Brain Tumors. 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI 2014) pp.1-4 doi: 10.1109/PRNI.2014.6858550
A. Tosi and A. Vellido (2014) Local metric and graph based distance for probabilistic dimensionality reduction. The workshop on Features and Structures (FEAST 2014) International Conference on Pattern Recognition (ICPR 2014), Stockholm, Sweden. (best poster award)
C.
König, R. Alquézar, A. Vellido (2014)
Finding class C GPCR subtype-discriminating
n-grams through feature selection, In Procs.
of the 8th International Conference
on Practical Applications of Computational
Biology & Bioinformatics (PACBB 2014),
pp.89-96.
M.I. Cárdenas, A. Vellido, J. Giraldo (2014)
Visual interpretation of class C GPCR subtype
overlapping from the nonlinear mapping of transformed
primary sequences. In Procs. of the 2nd
International Conference on Biomedical and Health
Informatics (IEEE BHI'14) pp.764-767.
V.J. Ribas Ripoll, A. Wojdel, A. Sáez de Tejada Cuenca,
J.C. Ruiz-Rodríguez, A. Ruiz-Sanmartín, M. de Nadal, E.
Romero, A. Vellido (2014)
Continuous blood pressure assessment from a
photoplethysmographic signal with Deep Belief Networks,
The FASEB Journal, 28(1), Supplement LB674.
M.I.
Cárdenas, A. Vellido, C. König, R. Alquézar and J.
Giraldo, Exploratory visualization of misclassified
GPCRs from their transformed unaligned sequences using
manifold learning techniques, In F. Ortuño, I. Rojas
(eds.): Procs. of the 2nd International
Work-Conference on Bioinformatics and Biomedical
Engineering (IWBBIO 2014)
pp.623-630.
A. Tosi, I. Olier, A. Vellido, Probability ridges and
distortion flows: Visualizing multivariate time series
using a variational Bayesian manifold learning method.
10th Workshop on Self-Organizing
Maps (WSOM 2014). Advances
in Intelligent Systems and Computing,
Vol.295, pp.55-64.
König, C., Vellido, A., Alquézar, R. and Giraldo, J. Misclassification of class C G-protein-coupled receptors as a label noise problem. In Proceedings of the 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014), Bruges, Belgium. pp. 695-700.
König, C., Cruz-Barbosa, R., Alquézar, R. and Vellido, A. (2013) SVM-Based Classification of Class C GPCRs from Alignment-Free Physicochemical Transformations of Their Sequences. 2nd International Workshop on Pattern Recognition in Proteomics, Structural Biology and Bioinformatics (PR PS BB 2013), 17th International Conference on Image Analysis and Processing (ICIAP), In A. Petrosino, L. Maddalena, P. Pala (Eds.): ICIAP 2013 Workshops, LNCS 8158, pp. 336–343, 2013, Springer.
Martín, À, Vellido, A. (2013) Cartogram-based data visualization using the Growing Hierarchical SOM, In K. Gibert, V. Botti and R. Reig-Bolaño (eds.) Artificial Intelligence Research and Development. Procs. of the 16th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2013), pp.249-252, IOS Press.
Cruz-Barbosa,
R., Vellido, A., Giraldo, J. (2013) Advances
in Semi-Supervised Alignment-Free
Classification of G-Protein-Coupled
Receptors, In Procs. of the
International Work-Conference on
Bioinformatics and Biomedical Engineering
(IWBBIO'13), Granada, Spain,
pp.759-766.
Ribas Ripoll, V.,
Romero, E., Ruiz-Rodríguez, J.C., Vellido,
A. (2013) A Quotient Basis Kernel for the
prediction of mortality in severe sepsis
patients. In Proceedings of the
21st European Symposium on Artificial Neural
Networks, Computational Intelligence and
Machine Learning (ESANN
2013),
Bruges, Belgium, pp.379-384.
Tosi, A., Vellido, A. (2013) Robust cartogram visualization of outliers in manifold learning, In Proceedings of the 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), Bruges, Belgium, pp.555-560.
García, D.L., Nebot, À. Vellido, A. (2013) Visualizing pay-per-view television customers churn using cartograms and flow maps, In Proceedings of the 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), Bruges, Belgium, pp.567-572.
P.J.G.
Lisboa, I.H. Jarman, T.A. Etchells, S.J. Chambers, D.
Bacciu, J. Whittaker, J.M. Garibaldi, S. Ortega-Martorell,
A. Vellido, I.O. Ellis (2012) Discovering Hidden Pathways
in Bioinformatics, LNCS/LNBI 7548, pp 49-60
V.J. Ribas, J.
Caballero López,
A. Sáez de Tejada, J.C. Ruiz-Rodríguez, A.
Ruiz-Sanmartín, J. Rello, A. Vellido (2012) On
the Use of Graphical Models to Study ICU Outcome
Prediction in Septic Patients Treated with Statins, LNCS/LNBI
7548, pp 98-111
M.I. Cárdenas, A. Vellido, I. Olier, X. Rovira, J. Giraldo (2012) Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree, LNCS/LNBI 7548, pp 136-149
Garcia, D.L., Vellido, A., Nebot, À. (2013) Telecommunication Customers Churn Monitoring Using Flow Maps and Cartogram Visualization.In GRAPP 2013 / IVAPP 2013 - Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Information Visualization Theory and Applications, pp.451-460, Barcelona, Spain.
Ortega-Martorell, S., Lisboa, P.J.G., Vellido, A., Simões,
R.V., Pumarola, M.,
Julià-Sapé, M., Arús, C. (2012) Unsupervised tumour area
delimitation in glioblastoma multiforme using non-negative
matrix factorisation of MRSI grids. European Society for
Magnetic resonance in Medicine and Biology Congress (ESMRMB 2012). Accepted for
oral presentation.
Ortega-Martorell, S. Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. (2012) Delimitation of the solid tumour area in glioblastomas using Non-Negative Matrix Factorization, In Procs. of the IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012), abstract.
Vilamala, A., Belanche,
L.A., and Vellido, A. (2012) Classifying malignant brain tumours from
1H-MRS data using Breadth Ensemble Learning. In Procs. of the
IEEE World Congress on Computational Intelligence (WCCI 2012)
International Joint Conference on Artificial Neural Networks (IJCNN 2012), Brisbane,
Australia, pp.2803-2810.
Ruiz, H., Ortega-Martorell, S., Jarman, I.H., Vellido, A., Romero, E., Martín, J.D. and Lisboa, P.J.G. (2012) Towards Interpretable Classifiers with Blind Signal Separation. In Procs. of the IEEE World Congress on Computational Intelligence (WCCI 2012) International Joint Conference on Artificial Neural Networks (IJCNN 2012), Brisbane, Australia, pp.3008-3016.
Tosi,
A., Vellido, A. (2012) Cartogram representation of the
batch-SOM magnification factor. In Proceedings of the
European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN 2012),
Bruges, Belgium, pp.203-208.
Vellido, A., Martín-Guerrero, J.D., Lisboa, P.J.G. (2012) Making machine learning models
interpretable. In
Proceedings of the European Symposium on Artificial Neural
Networks, Computational Intelligence and Machine Learning (ESANN 2012),
Bruges, Belgium, pp.163-172.
Ortega-Martorell, S.,
Lisboa, P.J.G., Vellido, A., Simões, R.V., Julià-Sapé, M., and
Arús, C. (2011) Brain tumor pathological area
delimitation through Non-negative Matrix Factorization, BioDM'
Workshop, The IEEE 11th International Conference on Data
Mining Workshops (ICDMW'11)
pp.1058-1063
Cruz-Barbosa,
R., Bautista-Villavicencio, D., Vellido, A. (2011) On the computation of
the Geodesic Distance with an application to dimensionality
reduction in a neuro-oncology problem. In Procs. of The 16th
Iberoamerican Congress on Pattern Recognition (CIARP 2011), LNCS 7042, pp.483-490.
Ribas,
V., Ruiz-Rodríguez, J.D., Wojdel, A., Caballero-López, J.,
Ruiz-Sanmartín A., Rello, J. and Vellido, A. (2011) Severe sepsis
mortality prediction with Relevance Vector Machines. In Procs.
of the 33rd Annual International Conference of the
IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp.100-103.
Arizmendi, C., Sierra, D.A., Vellido, A., Romero, E. (2011) Brain Tumour Classification Using Gaussian Decomposition and Neural Networks. In Procs. of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp.5645-5648.
Ortega-Martorell,
S., Olier, I., Vellido, A., Lisboa, P.J.G., El-Deredy, W. (2011) Comparing independent
component analysis and non-negative matrix factorisation in
the identification of event-related brain dynamics, 11th International
Conference on Cognitive Neuroscience (ICON XI), Abstract A066,
p.82.
Ortega-Martorell, S., Vellido, A., Lisboa, P.J.G., Julià-Sapé, M., and Arús, C. (2011) Spectral decomposition
methods for the analysis of MRS information from human brain
tumours, In Procs. of the 2011 International Joint Conference
on Neural Networks (IJCNN
2011), pp.3285-3292.
Cárdenas,
M.I., Vellido, A., Olier, I., Rovira, X., Giraldo, J. (2011) Visualization of the
phylogenetic structure of G Protein-Coupled Receptor sequences
using kernel and tree methods, Eigth International Meeting on
Computational
Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011)
Ribas, V.J., Caballero-López, J., Saez de Tejada, A., Ruiz-Rodríguez, J.C., Ruiz-Sanmartín, A., Rello, J., Vellido, A. (2011) Bayesian networks for
ICU outcome prediction in sepsis patients treated with statin
drugs, Eigth International Meeting on Computational
Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011).
Lisboa, P.J.G., Jarman, I.H., Etchells, T.A. , Chambers, S.J., Bacciu, D., Whittaker, J., Garibaldi, J. M., Ortega-Martorell, S., Vellido, A., and Ellis, I.H. (2011) Discovering hidden pathways in bioinformatics, Eigth International Meeting on Computational Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011).
Arizmendi,
C., Vellido, A., Romero, E., (2011)Binary Classification of Brain Tumours
Using a Discrete Wavelet Transform and Energy Criteria,
In Procs. of the 2nd IEEE Latin American Symposium on Circuits
and Systems (LASCAS 2011),
pp.1-4.
Vellido,
A., Cárdenas, M.I., Olier, I., Rovira, X., and Giraldo,
J. (2011) A probabilistic approach to the visual
exploration of G Protein-Coupled Receptor sequences, In Procs.
of the 19th European Symposiun on Artificial Neural Networks
(ESANN 2011),
pp.233-238.
Vellido, A., Martín, J.D.,
Rossi, F., and Lisboa, P.J.G. (2011) Seeing is believing: The importance of
visualization in real-world machine learning applications, In Procs. of the 19th European Symposiun
on Artificial Neural Networks (ESANN 2011), pp.219-226.
Cruz-Barbosa, R., Bautista-Villavicencio, D., and Vellido, A. (2011) Comparative diagnostic accuracy of linear and nonlinear feature extraction methods in a neuro-oncology problem. In Procs. of the 3rd Mexican Conference on Pattern Recognition (MCPR 2011) LNCS, Vol.6718, 2011, pp.34-41.
Ribas, V., Caballero-López, J., Ruiz-Rodríguez, J.C., Ruiz Sanmartín, A., Rello, J., and Vellido, A. (2011) On the use of decision trees for ICU outcome prediction in sepsis patients treated with statins. In Procs. of the IEEE Symposium Series on Computational Intelligence / IEEE Symposium on Computational Intelligence and Data Mining (IEEE SSCI CIDM 2011), pp.37-43.
Vellido,
A. Should you trust what you see? Inroads into data
visualization using generative topographic mapping. (2010) 3rd
International Conference of the ERCIM WG on Computing &
Statistics (ERCIM 2010),
London, U.K.
Arizmendi,
C., Hernández-Tamames, J., Romero, E., Vellido, A., del Pozo,
F. (2010) Diagnosis of Brain Tumours from
Magnetic Resonance Spectroscopy using Wavelets and Neural
Networks. In Procs. of the 32nd Annual International
Conference of the IEEE Engineering in Medicine and Biology
Society (EMBC 2010)
Buenos Aires, Argentina, pp.6074-6077
Colas,
F., Kok, J.N., and Vellido, A. (2010) Finding
Discriminative Subtypes of Aggressive Brain Tumours using
Magnetic Resonance Spectroscopy. In Procs. of the 32nd Annual
International Conference of the IEEE Engineering in Medicine
and Biology Society (EMBC
2010) Buenos Aires, Argentina
Ortega-Martorell, S., Olier, I., Vellido, A., Julià-Sapé, M., Arús, C. (2010) Spectral Prototype Extraction for the discrimination of glioblastomas from metastases in a SV 1H-MRS brain tumour database. ISMRM-ESMRMB Joint Annual Meeting.
Lisboa,
P.J.G., Vellido, A., Martín, J.D. (2010) Computational
Intelligence in biomedicine: Some contributions. 18th European Symposiun
on Artificial Neural Networks (ESANN 2010), 429-438.
Olier,
I.,
Amengual, J., Vellido, A. (2010) Segmentation of EMG time series using a
variational Bayesian approach for the robust estimation of
cortical silent periods. 18th European Symposiun on Artificial
Neural Networks (ESANN
2010), 439-444.
Olier,
I., Vellido, A., Giraldo, J. (2010) Kernel Generative Topographic Mapping. 18th European Symposiun
on Artificial Neural Networks (ESANN 2010), 481-486.
Ortega-Martorell,
S.,
Olier, I., Vellido, A., Julià-Sapé, M., Arús, C. (2010) Spectral Prototype
Extraction for dimensionality reduction in brain tumour
diagnosis. 18th European Symposiun on Artificial
Neural Networks (ESANN
2010), 445-450.
Cruz,
R., and Vellido, A., Semi-supervised Outcome Prediction for a
Type of Human Brain Tumour Using Partially Labeled MRS
Information. In Procs. of the Intelligent Data
Engineering and Automated Learning (IDEAL 2009) International
Conference, Lecture Notes in Computer Science, LNCS 5788, 168-175
Arizmendi, A., Vellido, A., Romero, E. (2009) Frequency Selection for the Diagnostic Characterization of Human Brain Tumours. In Procs. of the CCIA 2009.
Romero,
E., Vellido, A., Julià-Sapé, M, and Arús, C. (2009)
Discriminating glioblastomas from metastases in a SV 1H-MRS
brain tumour database. In Proceedings of the 26th Annual
Meeting of the European Society for Magnetic Resonance in
Medicine and Biology (ESMRMB
2009), Antalya,
Turkey, p.18.
Cruz, R., and Vellido, A. (2009) Comparative evaluation of Semi-Supervised Geodesic GTM. In The 4th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2009). LNAI 5573, pp.344-351.
Romero, E., Vellido, A., and Sopena, J.M. (2009) Feature selection with single-layer perceptrons for a multicentre 1H-MRS brain tumour database. In The 10th International Work-Conference on Artificial Neural Networks (IWANN 2009). LNCS 5517, pp.1013–1020.
Lisboa,
P.J.G., Romero, E., Vellido, A., Julià-Sapé, M., and
Arús, C. (2008) Classification, Dimensionality Reduction, and
Maximally Discriminatory Visualization of a Multicentre 1H-MRS
Database of Brain Tumors. In The Seventh International
Conference on Machine Learning and Applications (ICMLA'08), 613-618.
Cruz, R., Vellido, A. (2008) On the Improvement of the Mapping Trustworthiness and Continuity of a Manifold Learning Model. In Procs. of the 9th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2008). LNCS 5326, 266-273.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. (2008) Exploring outlierness
and its causes in a 1H-MRS brain tumour database.
In Proceedings of e-TUMOUR Workshop ‘Towards Brain Tumour
Classification by Molecular Profiling’, Valencia, Spain.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. (2008) Nonlinear
dimensionality reduction for the exploration of outliers in a
multicentre 1H-MRS database of brain tumours. In
Proceedings of the 25th Annual Meeting of the European Society
for Magnetic Resonance in Medicine and Biology (ESMRMB).
Cruz,
R., Vellido, A. (2008) Geodesic Generative Topographic Mapping.
In Proceedings of the 11th Ibero-American Conference on
Artificial Intelligence (IBERAMIA
2008). LNAI
5290, 113-122.
Cruz,
R., Vellido, A. Unfolding the Manifold in Generative
Topographic Mapping. In Proceedings of the 3rd International
Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008). LNAI 5271,
392-399 .
Nebot, A., Castro, F., Vellido, A., Julià-Sapé, M. and Arús, C. (2008) Rule-based assistance to brain tumour diagnosis using LR-FIR. In Procs. of the 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2008). LNAI 5178, Vol. II, 173-180.
Vellido, A., Julià-Sapé, M., Romero, E. and Arús, C. (2008) Exploratory characterization of outliers in a multi-centre 1H-MRS brain tumour dataset. In Procs. of the 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2008). LNAI 5178, Vol. II, 189-196.
Vellido,
A., Velazco, J.S. (2008) Assessment of the effect of noise on an
unsupervised feature selection method for Generative
Topographic Mapping. In 10th International Conference on
Enterprise Information Systems (ICEIS 2008).
Vellido, A., Velazco, J.S. (2008) The effect of noise and sample size on an unsupervised feature selection method for manifold learning. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 523-528.
Olier,
I., Vellido, A. (2008) On the benefits for model regularization
of a Variational formulation of GTM. In Procs. of the International Joint Conference on
Neural Networks (IJCNN 2008),
1569-1576.
Olier, I., Vellido, A. (2008) A Variational Formulation for GTM Through Time. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 517-522.
Vellido,
A., Biganzoli, E., Lisboa, P.J.G. (2008) Machine learning in
cancer research: implications for personalised medicine. In Procs. of the 16th
European Symposiun on Artificial Neural Networks (ESANN 2008), 55-64.
Romero, E., Julià-Sapé, M., Vellido, A.
(2008)
DSS-oriented
exploration of a multi-centre magnetic resonance spectroscopy
brain tumour dataset through visualization. In Procs. of the 16th
European Symposiun on Artificial Neural Networks (ESANN 2008), 95-100.
Cruz, R., Vellido, A. Two-Stage Clustering of a Human Brain Tumour Dataset Using Manifold Learning Models. In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2008, Funchal, Madeira, Portugal. INSTICC Press. pp.191-196.
Olier, I., Vellido, A. (2007) Variational GTM. In 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'07). Accepted.
Olier, I., Vellido, A. (2007) A Variational Bayesian Formulation for GTM: Theoretical Foundations. Technical Report LSI-07-33-R.Universitat Politècnica de Catalunya, UPC, Barcelona, Spain. (download)
Cruz, R., Vellido, A. (2007) On the Influence of Class Information in the Two-Stage Clustering of a Human Brain Tumour Dataset. In Procs. of the 6th Mexican Conference on Artificial Intelligence (MICAI 2007). LNAI 4827, 472-482. (pdf)
Cruz, R., Vellido, A. (2007) On the Initialization of Two-Stage Clustering with class-GTM. In 12th Conference of the Spanish Association for Artificial Intelligence (CAEPIA'07+TTIA). LNAI Vol.4788, 50-59. (pdf)
Cruz, R., Vellido, A. (2007) Evaluation of a Two-Stage Clustering Procedure Using Class Information in Generative Topographic Mapping. In I.Rojas Ruiz and H. Pomares Cintas (eds.) Actas del II Simposio de Inteligencia Computacional (IEEE SICO 2007), Thomson, pp.17-24.
García, D.L. ,
Vellido, A. and Nebot, A. (2007) Finding
relevant features for the churn analysis-oriented segmentation
of a telecommunications market. In I.Rojas Ruiz and H.
Pomares Cintas (eds.) Actas del II Simposio de Inteligencia
Computacional (IEEE SICO
2007), Thomson, pp.301-310.
Cruz, R., Vellido, A. (2007) Limits to the Use of Class Information in a GTM-based Two-Stage Clustering Procedure. In F.J.Ferrer-Troyano et al. (eds.), Actas del IV Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA 2007), Thomson, pp.303-312
Vellido, A., Lisboa, P.J.G. (2007) Neural networks and other machine learning methods in cancer research. In Procs. of IWANN 2007.LNCS 4507, 964-971.
García,
D.L.
, Vellido, A. and Nebot, A., (2007) Predictive Models in Churn
Data Mining: A Review. Technical Report LSI-07-4-R,
Universitat Politècnica de Catalunya, UPC, Barcelona, Spain.
García, D.L. , Vellido, A. and Nebot, A., (2007)
Identification of churn routes in the Brazilian
telecommunications market. In Procs. of the 15th European
Symposiun on Artificial Neural Networks, ESANN 2007,
585-590.
García, D.L, Vellido, A., and Nebot, A.
(2007) Customer Continuity Management as a Foundation for
Churn Data Mining. Technical Report LSI-07-2-R. Universitat
Politècnica de Catalunya, UPC, Barcelona, Spain.
Cruz, R. and Vellido, A., (2007) Elements of Generative Manifold Learning for semi-supervised tasks. Technical Report LSI-07-1-R. Universitat Politècnica de Catalunya, UPC, Barcelona, Spain.
Cruz, R. and Vellido, A., (2006) Clustering of brain tumours through constrained manifold learning using class information. Learning'06 International Conference. 'Between Learning and Data Mining' special session, 3rd of October, Vilanova i la Geltrú, Spain.
Spate, J., Gibert, K., Sànchez-Marrè, M., Frank, E., Comas, J., Athanasiadis, I., and Vellido, A. (2006) Data Mining as a Tool for Analysing Environmental Systems. Learning'06 International Conference. 'Between Learning and Data Mining' special session, 3rd of October, Vilanova i la Geltrú, Spain.
Poveda, J. and Vellido, A. (2006) Neural Network Models for Language Acquisition: A Brief Survey. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 1346-1357.
Olier, I. and Vellido, A. (2006) Time Series Relevance Determination through a topology-constrained Hidden Markov Model. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 40-47.
Vellido, A. , Etchells, T.A. , García, D.L. and Nebot, À. (2006) Describing customer loyalty to Spanish petrol stations through rule extraction. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 970-977.
Vellido, A. (2006) Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping. 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece. LNCS Vol.4132, 361-370. (download)
Cruz, R. and Vellido, A. (2006) On the improvement of brain tumour data clustering using class information, In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.
Olier, I. and Vellido, A. (2006) Capturing the Dynamics of Multivariate Time Series Through Visualization Using Generative Topographic Mapping Through Time, In proceedings of the 1st IEEE International Conference on Engineering of Intelligent Systems, ICEIS'2006, Islamabad, Pakistán, pp.492-497. (download)
Etchells,T.A., Nebot, A., Vellido, A., Lisboa, P.J.G., and Múgica, F.(2006) Learning what is important: feature selection and rule extraction in a virtual course. In Proceedings of the 14th European Symposium on Artificial Neural Networks, ESANN 2006, Bruges, Belgium, 401-406.
Etchells, T.A., Vellido, A., Martí, E., Lisboa, P.J.G., and Comas, J. (2006) On the prediction of the ecological status of human-altered streams and its rule-based interpretation. 3rd Biennial meeting of the International Environmental Modelling and Software Society, iEMSs'2006. Data Mining Workshop.
Vellido, A., Comas, J., Cruz, R., and Martí, E. (2006) Finding relevant features for the characterization of the ecological status of human altered streams using a constrained mixture model. 3rd Biennial meeting of the International Environmental Modelling and Software Society, iEMSs'2006. Data Mining Workshop.
Andrade, A., and Vellido, A. (2006) Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping, In Proc. of the 25th IASTED International ConferenceModelling, Identification, and Control (MIC'06), Feb.6-8, Lanzarote, Canary Islands, Spain, pp.507-512.(pdf)
Vellido, A., Castro, F., Nebot, A., and Múgica, F. (2006) Characterization of atypical virtual campus usage behavior through robust generative relevance analysis, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.183-188.
Nebot, A., Castro, F., Múgica, F., and Vellido, A. (2006) Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79. [Shortlisted for The Fifth International Competition of Ph.D. Students in the WBE Area]
(2005) Capturing the dynamics of multivariate time series through visualization using Generative Topographic Mapping Through Time. Technical Report LSI-05-52-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Detecting atypical student behaviour on an e-learning system, Accepted for oral presentation: VI Congreso Nacional de Informática Educativa; Simposio Nacional de Tecnologías de la Información y las Comunicaciones en la Educación, SINTICE’2005 (ADIE), Granada, Spain, September 2005.
Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Finding relevant features to characterize student behavior on an e-learning system, In: International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS 2005), Las Vegas, Nevada, USA, June 2005.
(2005) Comparative assessment of the robustness of missing data imputation through Generative Topographic Mapping, In Cabestany, J., Prieto, A., and Sandoval, F. (Eds.) Proc. of the IWANN 2005, Vilanova i la Geltru, Barcelona, Spain. LNCS Vol.3512, 771-778.
,Vellido, A., Lisboa, P.J.G., and Vicente,D. (2005) Handling outliers and missing data in brain tumor clinical assessment usign t-GTM. In Proc. of the European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, 121-126.
Vellido, A. and Lisboa, P.J.G. (2005) Functional topographic mapping for robust handling of outliers in brain tumour data. In Proc. of the European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, 133-138.
Vellido, A. (2005) Preliminary theoretical results on a feature relevance determination method for Generative Topographic Mapping. Technical Report LSI-05-13-R, Universitat Politècnica de Catalunya, UPC, Barcelona, Spain
Olier,
I., and Vellido, A. (2004) Assessing the robustness of
missing data imputation through Generative Topographic
Mapping. ACIA Newsletter, 31, 14-20.
Vellido, A. (2004) Missing data imputation through Generative Topographic Mapping as a mixture of t-distributions: Theoretical developments. Technical Report LSI-04-50-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A. (2004) Generative Topographic Mapping as a constrained mixture of Student t-distributions: Theoretical developments. Technical Report LSI-04-44-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vicente, D., Vellido, A., Martí, E., Comas, J., and Rodriguez-Roda, I. (2004), “Exploration of the ecological status of Mediterranean rivers: Clustering, visualizing and reconstructing streams data using Generative Topographic Mapping”. In W.I.T. Transactions on Information and Communication Technologies, Vol.33, 121-130.
Vellido, A., Olier, I., Martí, E., Comas, J., and Rodríguez-Roda, I. (2004) STREAMES project: Exploration of the ecological status of Mediterranean rivers using Generative Topographic Mapping. Poster presentation at BESAI 2004 - 4th ECAI Workshop on Binding Environmental Sciences and Artificial Intelligence. August 2004, Valencia, Spain.
Vellido, A., El-Deredy, W., and Lisboa, P.J.G. (2004) Studying embedded human EEG dynamics using Generative Topographic Mapping . Technical Report LSI-04-8-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A., and El-Deredy, W. (2004) Exploring dopamine-mediated reward processing through the analysis of EEG-measured gamma-band brain oscillations. Technical Report LSI-04-7-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A., El-Deredy, W., Gruber, T., Zald, D.H., McGlone, F.P., and Müller, M.M. (2003) Reward predictability and oscillatory brain processes. In The Annual Computational Neuroscience Meeting, CNS'2003. Poster presentation. Alicante, Spain.
Vellido, A. (2002) Neural networks for B2C
e-commerce analysis: some elements of best practice. In Proceedings
of the 4th International Conference On Enterprise
Information
Systems, ICEIS'2002, Ciudad
Real,
Spain.
Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) A systematic quantitative methodology for characterizing the business-to-consumer e-commerce market. ACM SIGBIO Newsletter, Vol.20(1), p.24.
Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) Segmenting the e-commerce market using the Generative Topographic Mapping. In Proceedings of the MICAI-2000, 470-481. Acapulco, México.
Lisboa, P.J.G., Wong, H., Vellido, A., Kirby, S.P.J., Harris, P. and Swindell, R. (1998) Survival of Breast Cancer Patients Following Surgery: a Detailed Assessment of the Multi-Layer Perceptron and Cox’s Proportional Hazard Model. In Proceedings of the World Congress on Computational Intelligence, IJCNN'1998, 112-116. Anchorage, Alaska, USA.
Lisboa, P.J.G., Vellido, A., Aung, H., El-Deredy, W., Lee, Y.Y.B. and Kirby, S.P.J. (1998) Quantification of uncertainty in tissue characterisation with NMR Spectra. In Proceedings of the 6th Scientific Meeting of the International Society for Magnetic Resonance in Medicine, Abstract 1851, Sidney, Australia.
Y.Y.B. Lee, A. Vellido, W. El-Deredy, S. Kirby, P. Lisboa (1998) Neural networks in practice-an example from magnetic resonance spectroscopy. In Proc. of the IEE Colloquium on Intelligent Methods in Healthcare and Medical Applications (Digest No. 1998/514)
Lisboa, P.J.G., El-Deredy, W., Vellido, A., Etchells, T. and Pountney, D.C. (1997) Automatic Variable Selection and Rule Extraction Using Neural Networks. In Proceedings of the 15th IMACS World Congress on Scientific Computation, Modelling and Applied Mathematics, 461-466, Berlin, Germany.
Lisboa, P.J.G, Branston, N.M., El-Deredy, W. and Vellido, A. (1997) Tissue Characterisation with NMR Spectroscopy; Current State and Future Prospects for the Application of Neural Networks Analysis. In Proceedings of the IEEE/INNS International Joint Conference on Neural Networks, IJCNN'1997, 1385-1390, Houston, USA, pp.1385-1390.
Lisboa, P.J.G., Vellido, A., El-Deredy, W. and Auer, D. (1997) Pattern Recognition Analysis of MRS:A Benchmark of Linear Statistical Methods and Neural Networks. In Proceedings of the 14th Annual Meeting of the European Society of Magnetic Resonance in Medicine and Biology, Abstract 224, Brussels, Belgium.
P. Lisboa,S. Kirby,A. Vellido,B. Lee (1997) Pattern recognition methods for MRS analysis and classification. In Proc. of the IEE Colloquium on Realising the Clinical Potential of Magnetic Resonance Spectroscopy: The Role of Pattern Recognition (Digest No: 1997/082)
Generic References on Computational Intelligence methods
Vellido, A. (2019) The importance of interpretability
and visualization in Machine Learning for applications
in medicine and health care. Neural Computing
& Applications, accepted. draft.
J.R.G.
Cárdenas, À. Nebot, F. Mugica, A. Vellido (2016) A
decision making support tool: The Resilience Management
Fuzzy Controller, In 2016 IEEE
Congress on Evolutionary
Computation (CEC / WCCI'16),
pp.2313-2320.
J.D.
Martín-Guerrero, J.P.G. Lisboa, A. Vellido
(2016) Physics and Machine Learning: Emerging
Paradigms. In Proceedings of the
24th European Symposium on
Artificial Neural Networks,
Computational Intelligence and
Machine Learning (ESANN 2016),
Bruges, Belgium,
pp.319-326. [draft]
A. Vilamala, A. Vellido, L. Belanche (2016) Bayesian Semi Non-negative Matrix Factorisation. In Proceedings of the 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2016), Bruges, Belgium. pp.195-200.
P.J.G. Lisboa,
J.D. Martín,
and A. Vellido
(2015) Making Nonlinear Manifold Learning Models
Interpretable: the Manifold Grand Tour. Expert
Systems with Applications, 42(22),
8982-8988.
A. Tosi, A. Vellido
(2014) Probabilistic Geometries as a tool for
Interpretability in Dimensionality Reduction Models, In
the 8th WiML Workshop, Advances in Neural
Information Processing Systems (NIPS 2014), Montreal, Canada.
A.
Tosi, S. Hauberg, A. Vellido, N. Lawrence (2014) Metrics
for probabilistic geometries, In Nevin L. Zhang,
Jin Tian (eds.) Proceedings of The 30th Conference on
Uncertainty in
Artificial Intelligence (UAI
2014),
AUAI Press Corvallis, Oregon, USA, pp.800-808.
A. Tosi and A. Vellido (2014) Local metric and graph based distance for probabilistic dimensionality reduction. The workshop on Features and Structures (FEAST 2014) International Conference on Pattern Recognition (ICPR 2014), Stockholm, Sweden. (best poster award)
A.
Tosi, I. Olier, A. Vellido (2014)
Probability ridges and distortion
flows: Visualizing multivariate time
series using a variational Bayesian
manifold learning method. 10th Workshop on
Self-Organizing Maps
(WSOM 2014). Advances
in Intelligent Systems and
Computing, Vol.295,
pp.55-64.
Martín, À, Vellido, A. (2013) Cartogram-based data visualization using the Growing Hierarchical SOM, In K. Gibert, V. Botti and R. Reig-Bolaño (eds.) Artificial Intelligence Research and Development. Procs. of the 16th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2013), pp.249-252, IOS Press.
Cruz-Barbosa, R. and Vellido, A. (2013) Generative manifold learning for the exploration of partially labeled data. Computación & Sistemas, 17(4), 641-653. doi: 10.13053/CyS-17-4-2013-014
Tosi, A., Vellido, A. (2013) Robust cartogram visualization of outliers in manifold learning, In Proceedings of the 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), Bruges, Belgium, pp.555-560.
Vellido,
A., García,
D., Nebot, À.
(2013)
Cartogram
Visualization
for Nonlinear
Manifold
Learning
Models. Data
Mining and
Knowledge
Discovery, 27(1):22-54,
doi: 10.1007/s10618-012-0294-6
Tosi,
A., Vellido, A. (2012) Cartogram representation of the
batch-SOM magnification factor. In Proceedings of the
European Symposium on Artificial Neural Networks,
Computational Intelligence and Machine Learning (ESANN 2012),
Bruges, Belgium, pp.203-208.
Vellido, A., Martín-Guerrero, J.D., Lisboa, P.J.G. (2012) Making machine learning models interpretable. In Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), Bruges, Belgium, pp.163-172.
Vellido, A., Martín, J.D.,
Rossi, F., and Lisboa, P.J.G. (2011) Seeing is believing: The importance of
visualization in real-world machine learning applications, In Procs. of the 19th European Symposiun
on Artificial Neural Networks (ESANN 2011), pp.219-226.
Vellido,
A. (2010) Should you trust what you see? Inroads into data
visualization using generative topographic mapping. (2010) 3rd
International Conference of the ERCIM WG on Computing &
Statistics (ERCIM 2010),
London, U.K.
Olier,
I., Vellido, A., Giraldo, J. (2010) Kernel Generative Topographic Mapping. 18th European Symposiun
on Artificial Neural Networks (ESANN 2010), pp.481-486.
Cruz,
R., Vellido, A. Semi-Supervised Geodesic Generative
Topographic Mapping. (2010) Pattern Recognition Letters,
31(3), 202-209.
Olier,
I., Vellido, A. Clustering and Visualization of Multivariate
Time Series (2009) In Soria-Olivas, E. et al. (eds.) The Handbook of Research on
Machine Learning Applications and Trends: Algorithms,
Methods, and Techniques, Vol.I, ch.8, pp.176-194.
Information Science Reference, New York.
Cruz,
R.,
and Vellido, A. (2009) Comparative evaluation of
Semi-Supervised Geodesic GTM. In The 4th
International Conference on Hybrid Artificial Intelligence
Systems (HAIS 2009). LNAI 5573,
pp.344-351.
Schleif, F.-M., Biehl,
M., and Vellido, A. (2009) Advances in machine learning and
computational intelligence. Neurocomputing, 72(7-9), 1377-1378.
Olier, I., Vellido, A. (2008) Variational Bayesian Generative Topographic Mapping. Journal of Mathematical Modelling and Algorithms, 7(4), 371-387.
Olier,
I., Vellido, A. (2008) Advances in Clustering and
Visualization of Time Series using GTM Through Time. Neural
Networks, 21(7), 904-913. preprint.
Cruz, R., Vellido, A. (2008) On the Improvement of the Mapping Trustworthiness and Continuity of a Manifold Learning Model. In Procs. of the 9th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2008). LNCS 5326, 266-273.
Cruz,
R., Vellido, A. (2008) Geodesic Generative Topographic Mapping.
In Proceedings of the 11th Ibero-American Conference on
Artificial Intelligence (IBERAMIA
2008). LNAI
5290, 113-122.
Cruz,
R., Vellido, A. (2008) Unfolding the Manifold in Generative
Topographic Mapping. In Proceedings of the 3rd International
Workshop on Hybrid Artificial Intelligence Systems (HAIS 2008). LNAI 5271,
392-399
Vellido,
A., Velazco, J.S. (2008) Assessment of the effect of noise on
an unsupervised feature selection method for Generative
Topographic Mapping. In 10th International Conference on
Enterprise Information Systems (ICEIS 2008). Accepted.
Vellido, A., Velazco, J.S. (2008) The effect of noise and sample size on an unsupervised feature selection method for manifold learning. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 523-528.
Olier,
I., Vellido, A. (2008) On the benefits for model
regularization of a Variational formulation of GTM. In Procs. of the International Joint Conference on
Neural Networks (IJCNN 2008),
1569-1576.
Olier, I., Vellido, A. (2008) A Variational Formulation for GTM Through Time. In Procs. of the International Joint Conference on Neural Networks (IJCNN 2008), 517-522.
Cruz, R., Vellido, A. (2008)
Two-Stage Clustering of a Human Brain Tumour Dataset Using
Manifold Learning Models. In International Conference on
Bio-inspired Systems and Signal Processing, BIOSIGNALS 2008, Funchal,
Madeira, Portugal, 191-196.
Olier, I., Vellido, A. Variational GTM. (2007) In 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'07). Accepted.
Olier, I., Vellido, A. (2007) A Variational Bayesian
Formulation for GTM: Theoretical Foundations. Technical Report
LSI-07-33-R.Universitat Politècnica de Catalunya,
UPC, Barcelona, Spain. (download)
Cruz, R., Vellido, A. (2007) On the Initialization of Two-Stage Clustering with class-GTM. In 12th Conference of the Spanish Association for Artificial Intelligence (CAEPIA'07+TTIA). LNAI Vol.4788, 50-59. (pdf)
Cruz, R., Vellido, A. (2007) Evaluation of a Two-Stage Clustering Procedure Using Class Information in Generative Topographic Mapping. In I.Rojas Ruiz and H. Pomares Cintas (eds.) Actas del II Simposio de Inteligencia Computacional (IEEE SICO 2007), Thomson, pp.17-24.
Cruz,
R., Vellido, A. (2007) Limits to the Use of Class Information
in a GTM-based Two-Stage Clustering Procedure. In F.J.Ferrer-Troyano et
al. (eds.), Actas del IV
Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA 2007), Thomson,
pp.303-312
Cruz, R. and
Vellido, A., (2007) Elements of Generative Manifold Learning
for semi-supervised tasks. Technical Report LSI-07-1-R.
Universitat Politècnica de Catalunya, UPC, Barcelona, Spain.
Vellido, A. (2006) Missing data imputation through GTM as a mixture of t-distributions. Neural Networks, 19(10), 1624-1635. (download)
Olier, I. and Vellido, A. (2006) Time Series Relevance Determination through a topology-constrained Hidden Markov Model. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 40-47.
Vellido, A. (2006) Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping. 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece. LNCS Vol.4132, 361-370. (download)
Olier, I. and Vellido, A. (2006) Capturing the Dynamics of Multivariate Time Series Through Visualization Using Generative Topographic Mapping Through Time, In proceedings of the 1st IEEE International Conference on Engineering of Intelligent Systems, ICEIS'2006, Islamabad, Pakistán, pp.492-497. (download)
(2005) Capturing the dynamics of multivariate time series through visualization using Generative Topographic Mapping Through Time. Technical Report LSI-05-52-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
(2005) Comparative assessment of the robustness of missing data imputation through Generative Topographic Mapping, In Cabestany, J., Prieto, A., and Sandoval, F. (Eds.) Proc. of the IWANN 2005, Vilanova i la Geltru, Barcelona, Spain. LNCS Vol.3512, 787-794.
Vellido, A. (2005) Preliminary theoretical results on a feature relevance determination method for Generative Topographic Mapping. Technical Report LSI-05-13-R, Universitat Politècnica de Catalunya, UPC, Barcelona, Spain
Olier, I., and Vellido, A. (2004) Assessing the robustness of missing data imputation through Generative Topographic Mapping. ACIA Newsletter, 31, 14-20.
Vellido, A. (2004) Missing data imputation through Generative Topographic Mapping as a mixture of t-distributions: Theoretical developments. Technical Report LSI-04-50-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A. (2004) Generative Topographic Mapping as a constrained mixture of Student t-distributions: Theoretical developments. Technical Report LSI-04-44-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A., El-Deredy, W., and Lisboa, P.J.G. (2003) Selective Smoothing of the Generative Topographic Mapping. IEEE Transactions on Neural Networks, 14(4), 847-852
Lisboa. P.J.G., Vellido, A. and Wong, H. (2000) Bias reduction in skewed binary classification with Bayesian neural networks. Neural Networks, 13, 407-410.
Lisboa, P.J.G., El-Deredy, W., Vellido, A., Etchells, T. and Pountney, D.C. (1997) Automatic Variable Selection and Rule Extraction Using Neural Networks. In Proceedings of the 15th IMACS World Congress on Scientific Computation, Modelling and Applied Mathematics, 461-466, Berlin, Germany.
Medical & Bio- Applications
Vellido, A. (2019) The importance of interpretability
and visualization in Machine Learning for applications
in medicine and health care. Neural Computing
& Applications, accepted. draft.
Aushev,
A., Ribas Ripoll, V., Vellido, A.,
Aletti, F., Bollen Pinto, B.,
Bendjelid, K., Herpain, A., Hendrik
Post, E. Romay Medina, E., Ferrer,
R., Baselli, G. (2018) Feature
selection for the accurate
prediction of septic and cardiogenic
shock ICU mortality in the acute
phase. PLoS ONE,
13(11): e0199089.
https://doi.org/10.1371/journal.pone.0199089.
Bilal,
A, Vellido, A, Ribas, V (2018) Enabling
interpretation of the outcome of a human obesity
prediction machine learning analysis from genomic data.
In procs. of the 15th International Conference on
Computational Intelligence methods for Bioinformatics
and Biostatistics (CIBB
2018) Lisbon,
Portugal.
Vellido A (2018) Societal
Issues Concerning the Application of
Artificial Intelligence in Medicine. Kidney
Diseases,
in press, available online, free
access
https://doi.org/10.1159/000492428.
Ribas Ripoll, V., Vellido, A. (2018) Blood pressure assessment with differential pulse transit time and deep learning: a proof of concept. Kidney Diseases; DOI: 10.1159/000493478
Hueso
M, Vellido A (2018)
Artificial
Intelligence and Dialysis.
Kidney Diseases;
DOI:
10.1159/000493933
König,
C., Shaim, I. , Vellido, A., Romero, E., Alquézar, R.,
Giraldo, J. (2018) Using
machine learning tools for protein database
biocuration assistance, Scientific Reports,
8:10148.
Bacciu,
D., Lisboa, P.J., Martín, J.D., Stoean, R. and Vellido,
A. (2018)
Bioinformatics
and medicine in the era of Deep Learning. In
Proceedings of the 26th European Symposium on Artificial
Neural Networks, Computational Intelligence and Machine
Learning (ESANN 2018), Bruges, Belgium,
pp.345-354.
Bilal,
A., Vellido, A., Ribas, V. (2018) Big
data analytics for obesity prediction. In 21st International
Conference of the Catalan Association for Artificial
Intelligence (CCIA
2017) Roses,
Spain. Accepted.
Hueso M, Vellido A, Montero N, Barbieri C, Ramos R, Angoso M, Cruzado JM, Jonsson A (2018) Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy. Kidney Diseases; 4:1-9. open access.
Vellido
A, Ribas V, Subirats L, Morales C, Ruiz Sanmartín A,
Ruiz Rodríguez JC (2018) Machine
Learning for Critical Care: State-of-the-Art and a
Sepsis Case Study, BioMedical Engineering
OnLine, 17(S1):135.
König C, Alquézar R,
Vellido A, Giraldo J (2018)
Systematic analysis of primary sequence domain segments
for the discrimination between class C GPCR subtypes, Interdisciplinary
Sciences: Computational Life Sciences,
10(1), 43-52.
Y. Hernández–Villegas, V. Mocioiu,
D. Ulinic, S.P. Kyathanahally, A. Vellido, C. Arús, M.
Julià-Sapé (2017) Automated quality control of magnetic
resonance spectra of brain tumors by Convex Non-negative
Matrix Factorization. In 34th Annual Scientific Meeting
of the European Society for Magnetic Resonance in
Medicine and Biology (ESMRMB), Barcelona, Spain.
A. Shkurin, A. Vellido (2017) Using random forests for assistance in the curation of G-protein coupled receptor databases. BioMedical Engineering OnLine, 16(Suppl 1):75
C. König, R. Alquézar, A. Vellido, J. Giraldo (2017) Discovering subtype specific n-gram motifs in class C GPCR N-termini. In Recent Advances in Artificial Intelligence Research and Development: Proceedings of the 20th International Conference of the Catalan Association for Artificial Intelligence, Deltebre, Terres de L'Ebre, Spain, October 25-27, 2017 (Vol. 300, p. 116). IOS Press.
C.
König, R.
Alquézar, A.
Vellido, J.
Giraldo (2017)
Topological
sequence
segments
discriminate
between class
C GPCR
subtypes. In 11th
International
Conference on
Practical
Applications
of
Computational
Biology &
Bioinformatics
(PACBB 2017),
Porto,
Portugal.
Accepted
A. Vellido, V. Ribas, C. Morales, A. Ruiz Sanmartín, J.C. Ruiz-Rodríguez (2017) Machine Learning for Critical Care: An Overview and a Sepsis Case Study. In I. Rojas and F. Ortuño (Eds.): Procs. of the 5th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2017), Granada, Spain. Part I, LNBI 10208, pp.15-30, Springer. doi: 10.1007/978-3-319-56148-6_2.
C.
Morales, A. Vellido, V. Ribas (2016)
Applying Conditional Independence
Maps to improve Sepsis Prognosis.
Data Mining in Biomedical
Informatics and Healthcare (DMBIH)
Workshop. IEEE International
Conference on Data Mining (ICDM
2016), accepted.
M.I. Cárdenas, A. Vellido and J. Giraldo (2016) Visual exploratory assessment of class C GPCR extracellular domains discrimination capabilities, In Procs. of the 10th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB'16) Advances in Intelligent Systems and Computing series, Vol.477, Springer, pp.31-39.
V.
Mocioiu, N.M. Pedrosa de Barros, S. Ortega-Martorell,J.
Slotboom, U. Knecht, C. Arús, A. Vellido and M.
Julià-Sapé (2016) A machine learning pipeline for
supporting differentiation of glioblastomas from single
brain metastases, In
Proceedings of the 24th European Symposium
on Artificial Neural Networks,
Computational Intelligence and Machine
Learning (ESANN 2016),
Bruges, Belgium.
pp.247-252.
A.
Shkurin and A. Vellido, Random Forests for quality
control in G-Protein Coupled Receptor databases, In Bioinformatics
and Biomedical Engineering (F. Ortuño, I.Rojas,
eds.) Proceedings of the 4th International Conference, IWBBIO
2016, Granada, Spain, April 20-22, 2016, LNCS/LNBI
9656, pp 707-718.
C König, R Alquézar, A Vellido, J Giraldo (2015) The Extracellular N-terminal Domain Suffices to Discriminate Class C G Protein-Coupled Receptor Subtypes from n-Grams of their Sequences, In: Procs. of the International Joint-Conference on Artificial Neural Networks (IJCNN 2015), Killarney, Ireland, pp.2330-2336.
C.L.
König, M.I.
Cárdenas, J.
Giraldo, R.
Alquezar, A.
Vellido (2015)
Label noise in
subtype
discrimination
of class C
G-protein
coupled
receptors: A
systematic
approach to
the analysis
of
classification
errors. BMC
Bioinformatics,
16(1):314.
open
access
M.I.
Cárdenas, A.
Vellido, C.
König, R.
Alquézar and
J. Giraldo
(2015) Visual
Characterization
of
Misclassified
Class C GPCRs
through
Manifold-based
Machine
Learning
Methods.
Genomics
and
Computational
Biology,
Accepted
C König, R Alquézar, A Vellido, J Giraldo (2015) The Extracellular N-terminal Domain Suffices to Discriminate Class C G Protein-Coupled Receptor Subtypes from n-Grams of their Sequences, In: Procs. of the International Joint-Conference on Artificial Neural Networks (IJCNN 2015), Killarney, Ireland, pp.2330-2336.
A. Vellido, C. Halka, À. Nebot (2015) A Weighted Cramer's V Index for the Assessment of Stability in the Fuzzy Clustering of Class C G Protein-Coupled Receptors. In F. Ortuño and I. Rojas (Eds.): IWBBIO 2015, Part I, LNCS 9043, pp. 536--547, Springer
R.
Cruz-Barbosa,
A. Vellido, J.
Giraldo
(2015)
The influence
of
alignment-free
sequence
representations
on the
semi-supervised
classication
of Class C G
Protein-Coupled
Receptors. Medical
&
Biological
Engineering
&
Computing, 53(2), 137-149, available
online
from Nov 2014.
C. König, R. Alquézar, A.
Vellido and J. Giraldo (2014) Finding class C GPCR
subtype-discriminating n-grams through feature selection. Journal
of Integrative Bioinformatics, 11(3):254.
doi: 10.2390/biecoll-jib-2014-254.
M.I. Cárdenas, A. Vellido, J. Giraldo (2014) Exploratory visualization of Metabotropic Glutamate Receptor subgroups through manifold learning. 17th International Conference of the Catalan Association of Artificial Intelligence (CCIA 2014) In L. Museros et al. (Eds.) Artificial Intelligence Research and Development, IOS Press, pp.269-272.
A. Vilamala, Ll. Belanche, A. Vellido (2014) A MAP approach for Convex Non-negative Matrix Factorization in the Diagnosis of Brain Tumors. 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI 2014) pp.1-4 doi: 10.1109/PRNI.2014.6858550
C.
König, R. Alquézar, A. Vellido (2014)
Finding class C GPCR subtype-discriminating
n-grams through feature selection, In Procs.
of the 8th International Conference
on Practical Applications of Computational
Biology & Bioinformatics (PACBB 2014),
pp.89-96.
M.I. Cárdenas, A. Vellido, J. Giraldo (2014)
Visual interpretation of class C GPCR subtype
overlapping from the nonlinear mapping of transformed
primary sequences. In Procs. of the 2nd
International Conference on Biomedical and Health
Informatics (IEEE BHI'14) pp.764-767.
V.J. Ribas Ripoll, A. Wojdel, A. Sáez de Tejada Cuenca,
J.C. Ruiz-Rodríguez, A. Ruiz-Sanmartín, M. de Nadal, E.
Romero, A. Vellido (2014)
Continuous blood pressure assessment from a
photoplethysmographic signal with Deep Belief Networks,
The FASEB Journal, 28(1), Supplement LB674.
V. Ribas, A. Vellido, E. Romero and J.C. Ruiz-Rodríguez (2014) Sepsis Mortality Prediction with Quotient Basis Kernels. Artificial Intelligence in Medicine, 61(1), 45-52. DOI:10.1016/j.artmed.2014.03.004
M.I.
Cárdenas, A. Vellido, C. König, R. Alquézar and J.
Giraldo (2014)
Exploratory visualization of misclassified GPCRs from
their transformed unaligned sequences using manifold
learning techniques, In F. Ortuño, I. Rojas (eds.):
Procs. of the 2nd International
Work-Conference on Bioinformatics and Biomedical
Engineering (IWBBIO 2014)
pp.623-630.
C.
Arizmendi, D.A. Sierra, A. Vellido and E.Romero (2014)
Automated classification of brain tumours from short
echo time in vivo MRS data
using Gaussian decomposition
and Bayesian Neural Networks, Expert Systems with
Applications, 41(11), 5296-5307.
doi: http://dx.doi.org/10.1016/j.eswa.2014.02.031.
König, C., Vellido, A., Alquézar, R. and Giraldo, J. (2014) Misclassification of class C G-protein-coupled receptors as a label noise problem. In Proceedings of the 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014), Bruges, Belgium. pp. 695-700.
Ortega-Martorell, S., Ruiz, H., Vellido, A., Olier, I., Romero, E., Julià-Sapé, M., Martín, J.D. , Jarman, I.H., Arús, C., Lisboa, P.J.G. (2013) A novel semi-supervised methodology for extracting tumor type-specific MRS sources in human brain data, PLoS ONE, 8(12): e83773.
Vilamala,
A., Lisboa, P.J.G.,
Ortega-Martorell,
S., Vellido, A.
(2013)
Discriminant
Convex
Non-negative
Matrix
Factorization
for the
Classification
of Human Brain
Tumours, Pattern
Recognition
Letters,
34(14),
1734–1747.
König,
C.,
Cruz-Barbosa,
R., Alquézar,
R. and
Vellido, A.
(2013)
SVM-Based
Classification
of Class C
GPCRs from
Alignment-Free
Physicochemical
Transformations
of Their
Sequences. 2nd
International
Workshop on
Pattern
Recognition in
Proteomics,
Structural
Biology and
Bioinformatics
(PR PS BB
2013),
17th
International
Conference on
Image Analysis
and Processing
(ICIAP), In A.
Petrosino, L.
Maddalena, P.
Pala (Eds.):
ICIAP 2013
Workshops,
LNCS 8158,
pp. 336–343,
2013, Springer.
Cruz-Barbosa,
R., Vellido,
A., Giraldo,
J. (2013) Advances
in
Semi-Supervised
Alignment-Free
Classification
of
G-Protein-Coupled
Receptors,
In Procs. of
the
International
Work-Conference
on
Bioinformatics
and Biomedical
Engineering (IWBBIO'13),
Granada,
Spain,
pp.759-766.
Ribas
Ripoll, V.,
Romero, E.,
Ruiz-Rodríguez,
J.C.,
Vellido,
A. (2013) A
Quotient Basis
Kernel for the
prediction of
mortality in
severe sepsis
patients. In
Proceedings of
the 21st
European
Symposium on
Artificial
Neural
Networks,
Computational
Intelligence
and Machine
Learning (ESANN
2013),
Bruges,
Belgium,
pp.379-384.
Ortega-Martorell,
S., Lisboa, P.J.G.,
Vellido, A., Simões, R.V.,
Pumarola, M., Julià-Sapé, M., Arús, C.
(2012) Convex
Non-Negative Matrix Factorization for
Brain Tumor Delimitation from MRSI Data,
PLoS ONE, 7(10):e47824.
P.J.G. Lisboa, I.H.
Jarman, T.A. Etchells, S.J. Chambers, D. Bacciu, J.
Whittaker, J.M. Garibaldi, S. Ortega-Martorell, A.
Vellido, I.O. Ellis (2012) Discovering Hidden Pathways in
Bioinformatics, LNCS/LNBI 7548, pp 49-60
V.J. Ribas, J.
Caballero López,
A. Sáez de Tejada, J.C. Ruiz-Rodríguez, A.
Ruiz-Sanmartín, J. Rello, A. Vellido (2012) On
the Use of Graphical Models to Study ICU Outcome
Prediction in Septic Patients Treated with Statins, LNCS/LNBI
7548, pp 98-111
M.I. Cárdenas, A. Vellido,
I. Olier, X. Rovira, J. Giraldo (2012)
Complementing Kernel-Based Visualization of Protein Sequences
with Their Phylogenetic Tree, LNCS/LNBI 7548, pp
136-149
Ortega-Martorell, S., Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. (2012) Unsupervised tumour area delimitation in glioblastoma multiforme using non-negative matrix factorisation of MRSI grids. European Society for Magnetic resonance in Medicine and Biology Congress (ESMRMB 2012). Accepted for oral presentation.
Ortega-Martorell, S. Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. (2012) Delimitation of the solid tumour area in glioblastomas using Non-Negative Matrix Factorization, In Procs. of the IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012), abstract.
Vilamala, A., Belanche,
L.A., and Vellido, A. (2012) Classifying malignant brain tumours from
1H-MRS data using Breadth Ensemble Learning. In Procs. of the
IEEE World Congress on Computational Intelligence (WCCI 2012)
International Joint Conference on Artificial Neural Networks (IJCNN 2012), Brisbane,
Australia, pp.2803-2810.
Ruiz,
H., Ortega-Martorell, S., Jarman, I.H., Vellido, A., Romero,
E., Martín, J.D. and Lisboa, P.J.G. (2012) Towards
Interpretable Classifiers with Blind Signal Separation. In Procs. of the IEEE World
Congress on Computational Intelligence (WCCI 2012) International
Joint Conference on Artificial Neural Networks (IJCNN 2012), Brisbane,
Australia, pp.3008-3016.
Ortega-Martorell,
S., Lisboa, P.J.G., Vellido, A.,Julià-Sapé, M., Arús, C. (2012) Non-negative
Matrix Factorisation methods for the spectral decomposition of
MRS data from human brain tumours. BMC Bioinformatics, 13:38.
(draft)
Vellido,
A., Romero, E., Julià-Sapé, M., Majós, C.,
Moreno-Torres, À., and Arús, C. (2012) Robust
discrimination of glioblastomas from metastatic brain tumors
on the basis of single-voxel proton MRS. NMR
in Biomedicine. 25(6):819–828.
Ribas,
V.J., Ruiz-Rodríguez, J.C., and Vellido, A.
(2012) Intelligent management of sepsis in the intensive care
unit. In: R. Magdalena-Benedito, E. Soria, J. Guerrero
Martínez, J. Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.1-16, doi:10.4018/978-1-4666-1803-9.ch001
Arizmendi,
C.J.,
Vellido,
A.,
Romero, (2012) E. Preprocessing MRS Information for
Classification of Human Brain Tumours. In: R.
Magdalena-Benedito, E. Soria, J. Guerrero Martínez, J.
Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.29-49, doi: 10.4018/978-1-4666-1803-9.ch003
Cárdenas,
M.I.,
Vellido,
A.,
Olier, I., Rovira, X., Giraldo, J. (2012) Kernel Generative
Topographic Mapping of Protein Sequences. In: R.
Magdalena-Benedito, E. Soria, J. Guerrero Martínez, J.
Gómez-Sanchis and A.J. Serrano-López (eds.) Medical Applications of
Intelligent Data Analysis: Research Advancements, IGI
Global, 2012, pp.194-207, doi: 10.4018/978-1-4666-1803-9.ch013
Ribas, V.J., Vellido, A.,
Ruiz-Rodríguez, J.C., Rello, J. (2012) Severe sepsis mortality
prediction with logistic regression over latent factors. Expert
Systems
with Applications, 39(2), 1937-1943.
Arizmendi,
C.,
Vellido, A., Romero, E. (2012) Classification of human brain tumours
from MRS data using discrete wavelet transform and Bayesian
neural networks. Expert Systems with Applications, 39(5),
5223-5232.
Ortega-Martorell, S. Lisboa, P.J.G., Vellido, A., Simões, R.V., Pumarola, M., Julià-Sapé, M., Arús, C. (2012) Delimitation of the solid tumour area in glioblastomas using Non-Negative Matrix Factorization, In ISBI 2012, accepted
Vellido,
A., Romero, E., Julià-Sapé, M., Majós, C.,
Moreno-Torres, À., and Arús, C. (2012) Robust discrimination
of glioblastomas from metastatic brain tumors on the basis of
single-voxel proton MRS. NMR in Biomedicine.
Accepted for publication.
Ortega-Martorell, S., Lisboa, P.J.G.,
Vellido, A., Simões, R.V., Julià-Sapé, M., and Arús, C. (2011) Brain tumor
pathological area delimitation through Non-negative Matrix
Factorization, BioDM' Workshop, The IEEE 11th International
Conference on Data Mining Workshops (ICDMW'11) pp.1058-1063
Cruz-Barbosa,
R., Bautista-Villavicencio, D., Vellido, A. (2011) On the computation of
the Geodesic Distance with an application to dimensionality
reduction in a neuro-oncology problem. In Procs. of The 16th
Iberoamerican Congress on Pattern Recognition (CIARP 2011), LNCS 7042, pp.483-490.
Ribas,
V., Ruiz-Rodríguez, J.D., Wojdel, A., Caballero-López, J.,
Ruiz-Sanmartín A., Rello, J. and Vellido, A. (2011) Severe sepsis
mortality prediction with Relevance Vector Machines. In Procs.
of the 33rd Annual International Conference of the
IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp.100-103.
Arizmendi, C., Sierra, D.A., Vellido, A., Romero, E. (2011) Brain Tumour Classification Using Gaussian Decomposition and Neural Networks. In Procs. of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), pp.5645-5648.
Ortega-Martorell, S., Vellido, A., Lisboa, P.J.G., Julià-Sapé, M., and Arús, C. (2011) Spectral decomposition
methods for the analysis of MRS information from human brain
tumours, In Procs. of the 2011 International Joint Conference
on Neural Networks (IJCNN
2011), pp.3285-3292.
Cárdenas,
M.I., Vellido, A., Olier, I., Rovira, X., Giraldo, J. (2011) Visualization of the
phylogenetic structure of G Protein-Coupled Receptor sequences
using kernel and tree methods, Eigth International Meeting on
Computational
Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011)
Ribas, V.J., Caballero-López, J., Saez de Tejada, A., Ruiz-Rodríguez, J.C., Ruiz-Sanmartín, A., Rello, J., Vellido, A. (2011) Bayesian networks for
ICU outcome prediction in sepsis patients treated with statin
drugs, Eigth International Meeting on Computational
Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011).
Lisboa, P.J.G., Jarman, I.H., Etchells, T.A. , Chambers, S.J., Bacciu, D., Whittaker, J., Garibaldi, J. M., Ortega-Martorell, S., Vellido, A., and Ellis, I.H. (2011) Discovering hidden pathways in bioinformatics, Eigth International Meeting on Computational Intelligence Methods in Bioinformatics and Biostatistics, (CIBB 2011).
Arizmendi,
C., Vellido, A., Romero, E., (2011) Binary Classification of Brain Tumours
Using a Discrete Wavelet Transform and Energy Criteria,
In Procs. of the 2nd IEEE Latin American Symposium on Circuits
and Systems (LASCAS 2011),
pp.1-4.
Vellido,
A., Cárdenas, M.I., Olier, I., Rovira, X., and Giraldo,
J. (2011) A probabilistic approach to the visual
exploration of G Protein-Coupled Receptor sequences, In Procs.
of the 19th European Symposiun on Artificial Neural Networks
(ESANN 2011),
pp.233-238.
Cruz-Barbosa, R., Bautista-Villavicencio, D., and Vellido, A. (2011) Comparative diagnostic accuracy of linear and nonlinear feature extraction methods in a neuro-oncology problem. In Procs. of the 3rd Mexican Conference on Pattern Recognition (MCPR 2011) LNCS, Vol.6718, 2011, pp.34-41.
Ribas, V., Caballero-López, J., Ruiz-Rodríguez, J.C., Ruiz
Sanmartín, A., Rello, J., and Vellido, A. (2011) On the
use of decision trees for ICU outcome prediction in sepsis
patients treated with statins. In Procs. of the IEEE Symposium
Series on Computational Intelligence / IEEE Symposium on
Computational Intelligence and Data Mining (IEEE SSCI CIDM 2011), 37-43.
Cruz, R.,
Vellido, A. (2011) Semi-supervised analysis of human brain
tumours from partially labeled MRS information, using manifold
learning models. International
Journal of Neural Systems. 21(1): 17-29.
Arizmendi,
C., Hernández-Tamames, J., Romero, E., Vellido, A., del Pozo,
F., (2010) Diagnosis of Brain Tumours from Magnetic Resonance
Spectroscopy using Wavelets and Neural Networks. In Procs. of the 32nd
Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBC
2010) Buenos Aires, Argentina, pp.6074-6077.
Colas,
F., Kok, J.N., and Vellido, A. (2010) Finding Discriminative
Subtypes of Aggressive Brain Tumours using Magnetic Resonance
Spectroscopy. In Procs. of the 32nd Annual International
Conference of the
IEEE Engineering in Medicine and Biology Society (EMBC 2010) Buenos Aires,
Argentina
Lisboa,
P.J.G. Vellido, A. Tagliaferri, R.
Napolitano, F. Ceccarelli, M. Martin-Guerrero,
J.D. Biganzoli, E. (2010) Data Mining in Cancer
Research, IEEE Computational Intelligence Magazine,
5(1), 14-18
Ortega-Martorell, S., Olier, I., Vellido, A., Julià-Sapé, M., Arús, C. (2010) Spectral Prototype Extraction for the discrimination of glioblastomas from metastases in a SV 1H-MRS brain tumour database. ISMRM-ESMRMB Joint Annual Meeting.
Lisboa,
P.J.G., Vellido, A., Martín, J.D. (2010) Computational
Intelligence in biomedicine: Some contributions. 18th European Symposiun
on Artificial Neural Networks (ESANN 2010), 429-438.
Ortega-Martorell,
S.,
Olier, I., Vellido, A., Julià-Sapé, M., Arús, C. (2010) Spectral Prototype
Extraction for dimensionality reduction in brain tumour
diagnosis. 18th European Symposiun on Artificial
Neural Networks (ESANN
2010), 445-450.
González-Navarro,
F.F.,
Belanche-Muñoz, Ll.A., Romero, E., Vellido, A., Julià-Sapé,
M., Arús, C. (2010) Feature and model selection with
discriminatory visualization for diagnostic classification of
brain tumours. Neurocomputing, 73(4-6), 622-632.
Romero,
E., Vellido, A., Julià-Sapé, M, and Arús, C. (2009)
Discriminating glioblastomas from metastases in a SV 1H-MRS
brain tumour database. In Proceedings of the 26th Annual
Meeting of the European Society for Magnetic Resonance in
Medicine and Biology (ESMRMB
2009), Antalya, Turkey, p.18.
Vellido,
A.,
Romero, E., González-Navarro, F.F., Belanche-Muñoz, Ll.,
Julià-Sapé, M., Arús, C. (2009) Outlier exploration and
diagnostic classification of a multi-centre 1H-MRS
brain tumour database. Neurocomputing, 72(13-15), 3085-3097.
Cruz,
R., and Vellido, A., Semi-supervised Outcome Prediction for a
Type of Human Brain Tumour Using Partially Labeled MRS
Information. In Procs. of the Intelligent Data
Engineering and Automated Learning (IDEAL 2009) International
Conference, Lecture Notes in Computer Science, LNCS 5788, 168-175
Arizmendi, A., Vellido, A., Romero, E. (2009) Frequency Selection for the Diagnostic Characterization of Human Brain Tumours. In Procs. of the CCIA 2009.
Romero, E., Vellido, A., and Sopena, J.M. (2009) Feature selection with single-layer perceptrons for a multicentre 1H-MRS brain tumour database. In The 10th International Work-Conference on Artificial Neural Networks (IWANN 2009). LNCS 5517, pp.1013–1020.
Vellido, A., and Lisboa, P.J.G. (eds.) Investigating Human Cancer with Computational Intelligence Techniques. In KES Recent Research Results series. Future Technology Press. 2009. ISBN: 978-0-9561516-0-5
Vellido,
A. and Lisboa, P.J.G. (2009) Preface to Investigating Human Cancer with
Computational Intelligence Techniques. In KES Recent Research Results
series. Future Technology
Press, vii-viii.
Nebot,
A., Castro, F., Vellido, A., Julià-Sapé, M., and Arús, C.
(2009) Rule-based assistance to brain tumour diagnosis using
LR-FIR. In Investigating
Human Cancer with Computational Intelligence Techniques.
KES Recent Research Results series. Future Technology Press,
83-92.
Vellido, A., Julià-Sapé, M., Romero, E., and Arús, C. (2009) Exploratory characterization of a multi-centre 1H-MRS brain tumour database. In Investigating Human Cancer with Computational Intelligence Techniques. KES Recent Research Results series. Future Technology Press, 55-67.
Lisboa,
P.J.G., Romero, E., Vellido, A., Julià-Sapé, M., and
Arús, C. (2008) Classification, Dimensionality Reduction, and
Maximally Discriminatory Visualization of a Multicentre 1H-MRS
Database of Brain Tumors. In The Seventh International
Conference on Machine Learning and Applications (ICMLA'08), 613-618.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. (2008) Exploring outlierness
and its causes in a 1H-MRS brain tumour database. In
Proceedings of e-TUMOUR Workshop ‘Towards Brain Tumour
Classification by Molecular Profiling’, Valencia, Spain.
Vellido,
A., Julià-Sapé, M., Romero, E., and Arús, C. (2008) Nonlinear
dimensionality reduction for the exploration of outliers in a
multicentre 1H-MRS database of brain tumours.
In Proceedings of the 25th Annual Meeting of the European
Society for Magnetic Resonance in Medicine and Biology (ESMRMB).
Nebot,
A., Castro, F., Vellido, A., Julià-Sapé, M. and Arús, C.
(2008) Rule-based assistance to brain tumour diagnosis using
LR-FIR. In Procs. of the 12th International Conference on
Knowledge-Based and Intelligent Information & Engineering
Systems (KES2008). LNAI 5178, Vol. II,
173-180.
Vellido, A., Julià-Sapé, M., Romero, E. and Arús, C. (2008) Exploratory characterization of outliers in a multi-centre 1H-MRS brain tumour dataset. In Procs. of the 12th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2008). LNAI 5178, Vol. II, 189-196.
Vellido,
A., Biganzoli, E., Lisboa, P.J.G. (2008) Machine learning in
cancer research: implications for personalised medicine. In Procs. of the 16th
European Symposiun on Artificial Neural Networks (ESANN 2008), 55-64.
Romero, E., Julià-Sapé, M., Vellido, A.
(2008)
DSS-oriented
exploration of a multi-centre magnetic resonance spectroscopy
brain tumour dataset through visualization. In Procs. of the 16th
European Symposiun on Artificial Neural Networks (ESANN 2008), 95-100.
Cruz,
R., Vellido, A. Two-Stage Clustering of a Human Brain Tumour
Dataset Using Manifold Learning Models. In Proceedings of the
International Conference on Bio-inspired Systems and Signal
Processing, BIOSIGNALS 2008,
Funchal, Madeira, Portugal. INSTICC Press. pp.191-196.
Vellido, A., Lisboa, P.J.G.
(2008) Machine Learning in Human Cancer Research. In Svensson,
H.A. (Ed.): Neurocomputing Research Developments. Nova
Publishers, 163-180.
Cruz, R., Vellido, A. (2007) On the Influence of Class Information in the Two-Stage Clustering of a Human Brain Tumour Dataset. In Procs. of the 6th Mexican Conference on Artificial Intelligence (MICAI 2007). LNAI 4827, 472-482. (pdf)
Vellido, A., Andrade, A.O. (2007) Determination of feature relevance for the grouping of motor unit action potentials through a generative mixture model. Biomedical Signal Processing and Control, 2(2), 111-121.
Vellido, A., Lisboa, P.J.G.
(2007) Neural networks and other machine learning methods in
cancer research. In Procs. of IWANN 2007.LNCS
4507, 964-971.
Cruz, R. and Vellido, A. (2006) Clustering of brain tumours through constrained manifold learning using class information. Learning'06 International Conference. 'Between Learning and Data Mining' special session, 3rd of October, Vilanova i la Geltrú, Spain.
Cruz, R. and Vellido, A. (2006) On the improvement of brain tumour data clustering using class information, In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.
Vellido, A., Lisboa, P.J.G., and Vicente, D. (2006) Robust analysis of MRS brain tumour data using t-GTM. Neurocomputing, 69(7-9), 754-768. (pdf)
Andrade, A., and Vellido, A. (2006) Determining feature relevance for the grouping of motor unit action potentials through generative topographic mapping, In Proc. of the 25th IASTED International ConferenceModelling, Identification, and Control (MIC'06), Feb.6-8, Lanzarote, Canary Islands, Spain, pp.507-512. (pdf)
Vellido, A. and Lisboa, P.J.G. (2006) Handling outliers in brain tumour MRS data analysis through robust topographic mapping, Computers in Biology and Medicine, 36(10), 1049-1063. (download)
Vellido, A., Lisboa, P.J.G., and Vicente,D. (2005) Handling outliers and missing data in brain tumor clinical assessment usign t-GTM. In Proc. of the European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, 121-126.
Vellido, A. and Lisboa, P.J.G. (2005) Functional topographic mapping for robust handling of outliers in brain tumour data. In Proc. of the European Symposium on Artificial Neural Networks, ESANN 2005, Bruges, Belgium, 133-138.
Lisboa, P.J.G., Vellido, A. and Wong, H. (2000) Outstanding Issues for Clinical Decision Support with Neural Networks. In Artificial Neural Networks in Medicine and Biology. Springer, London, 63-71
Lisboa, P.J.G., Kirby, S.J.P., Vellido, A., Lee, Y.Y.B. and El-Deredy, W. (1998) Assessment of Statistical and Neural Network Methods in NMR Spectral Classification and Metabolite Selection. Nuclear Magnetic Resonance in Biomedicine, 11, 225-234.
Lisboa, P.J.G., Wong, H., Vellido, A., Kirby, S.P.J., Harris, P. and Swindell, R. (1998) Survival of Breast Cancer Patients Following Surgery: a Detailed Assessment of the Multi-Layer Perceptron and Cox’s Proportional Hazard Model. In Proceedings of the World Congress on Computational Intelligence, IJCNN'1998, 112-116. Anchorage, Alaska, USA.
Lisboa, P.J.G., Vellido, A., Aung, H., El-Deredy, W., Lee, Y.Y.B. and Kirby, S.P.J. (1998) Quantification of uncertainty in tissue characterisation with NMR Spectra. In Proceedings of the 6th Scientific Meeting of the International Society for Magnetic Resonance in Medicine, Abstract 1851, Sidney, Australia.
Y. Lee,A. Vellido,W. El-Deredy,S. Kirby,P. Lisboa (1998) Neural networks in practice-an example from magnetic resonance spectroscopy. In Proc. of the IEE Colloquium on Intelligent Methods in Healthcare and Medical Applications (Digest No. 1998/514)
Lisboa, P.J.G, Branston, N.M., El-Deredy, W. and Vellido, A. (1997) Tissue Characterisation with NMR Spectroscopy; Current State and Future Prospects for the Application of Neural Networks Analysis. In Proceedings of the IEEE/INNS International Joint Conference on Neural Networks, IJCNN'1997, 1385-1390, Houston, USA.
Lisboa, P.J.G., Vellido, A., El-Deredy, W. and Auer, D. (1997) Pattern Recognition Analysis of MRS:A Benchmark of Linear Statistical Methods and Neural Networks. In Proceedings of the 14th Annual Meeting of the European Society of Magnetic Resonance in Medicine and Biology, Abstract 224, Brussels, Belgium.
P. Lisboa,S. Kirby,A. Vellido,B. Lee (1997) Pattern recognition methods for MRS analysis and classification. In Proc. of the IEE Colloquium on Realising the Clinical Potential of Magnetic Resonance Spectroscopy: The Role of Pattern Recognition (Digest No: 1997/082)
Business Applications
A. Vellido, D.L. García (2017) Electricity rate planning for the current consumer market scenario through segmentation of consumption time series. In Artificial Intelligence in Power and Energy Systems (AIPES) 18th EPIA Conference on Artificial Intelligence, Porto, Portugal, LNCS 10423, pp. 295-306, Springer
D.L.
García, À. Nebot, A. Vellido (2017) Intelligent data
analysis approaches to churn as a business problem: a
survey. Knowledge and Information Systems,
51(3):719-774.
DOI: 10.1007/s10115-016-0995-z (draft)
Vellido,
A., García,
D.,Nebot, À.
Cartogram
Visualization
for Nonlinear
Manifold
Learning
Models. Data
Mining and
Knowledge
Discovery, 27(1):22-54.
doi:
10.1007/s10618-012-0294-6
García,
D.L., Nebot, À. Vellido,
A. (2013)
Visualizing pay-per-view
television customers churn using cartograms and flow maps,
In
Proceedings of the 21st European Symposium on
Artificial Neural Networks, Computational Intelligence
and Machine Learning (ESANN 2013), Bruges,
Belgium, pp.567-572.
Garcia, D.L., Vellido, A., Nebot, À. (2013) Telecommunication Customers Churn Monitoring Using Flow Maps and Cartogram Visualization. In GRAPP 2013 / IVAPP 2013 - Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Information Visualization Theory and Applications, pp.451-460, Barcelona, Spain.
García, D.L. , Vellido, A. and Nebot, A. (2007) Finding
relevant features for the churn analysis-oriented segmentation
of a telecommunications market. In I.Rojas Ruiz and H.
Pomares Cintas (eds.) Actas del II Simposio de Inteligencia
Computacional (IEEE SICO
2007), Thomson, pp.301-310.
García, D.L. , Vellido, A. and Nebot, A., (2007) Identification of churn routes in the Brazilian telecommunications market. In Procs. of the 15th European Symposiun on Artificial Neural Networks, ESANN 2007, 585-590.
García,
D.L.
, Vellido, A. and Nebot, A., (2007) Predictive Models in Churn
Data Mining: A Review. Technical Report LSI-07-4-R,
Universitat Politècnica de Catalunya, UPC, Barcelona, Spain.
García, D.L, Vellido, A., and Nebot, A.
(2007) Customer Continuity Management as a Foundation for
Churn Data Mining. Technical Report LSI-07-2-R. Universitat
Politècnica de Catalunya, UPC, Barcelona, Spain.
Vellido, A. , Etchells, T.A. , García, D.L. and Nebot, À. (2006) Describing customer loyalty to Spanish petrol stations through rule extraction. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 970-977.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2002) Characterizing and Segmenting the On-Line Customer Market Using Neural Networks. In E-Commerce and Intelligent Methods. Heidelberg: Springer-Verlag, 101-119
Vellido, A. (2002) Neural networks for B2C e-commerce analysis: some elements of best practice. In Proceedings of the 4th International Conference On Enterprise Information Systems (ICEIS'2002) Ciudad Real, Spain.
Vellido, A and Lisboa, P.J.G (2001) An electronic commerce application of the Bayesian Framework for MLPs: the Effect of Marginalization and ARD. Neural Computing & Applications. 10(1)
Lisboa, P.J.G., Vellido, A. and Edisbury, B. (Editors, 2000) Business Applications of Neural Networks. Singapore: World Scientific.
Lisboa, P.J.G., Vellido, A. (2000) Preface: Business Applications of Neural Networks. In Business Applications of Neural Networks. Singapore: World Scientific.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) Characterizing and segmenting the business-to-consumer e-commerce market using neural networks. In Business Applications of Neural Networks. Singapore: World Scientific.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) The Generative Topographic Mapping as a principled model for data visualization and market segmentation: an electronic commerce case study. International Journal of Computers, Systems, and Signals. 1(2), 119-138.
Vellido, A, Lisboa, P.J.G and Meehan, K. (2000) Quantitative characterization and prediction of on-line purchasing behaviour: a latent variable approach. International Journal of Electronic Commerce, 4(4), 83-104.
Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) Segmenting the e-commerce market using the Generative Topographic Mapping. In Proceedings of the MICAI-2000, 470-481. Acapulco, México.
Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) A systematic quantitative methodology for characterizing the business-to-consumer e-commerce market. ACM SIGBIO Newsletter, Vol.20(1), p.24.
Vellido, A., Lisboa, P.J.G and Vaughan, J.
(1999) Neural
networks
in business: a survey of applications (1992-1998) Expert
Systems
with Applications. 17, 51-70.
Vellido, A., Lisboa, P.J.G and Meehan, K. (1999) Segmentation of the on-line shopping market using neural networks. Expert Systems with Applications. 17, 303-314.
Environmental modelling applications
X. Cipriano, A. Vellido, J. Cipriano, J. Martí, S. Danov (2017) Application of clustering and simulation methods for the analysis of socio-economical and technical factors influencing the energy refurbishment of neighbourhoods. Energy Efficiency, 10(2), 359-382. doi: 10.1007/s12053-016-9460-9
Vellido, A., Martí, E., Comas, J., Rodríguez-Roda, I., and Sabater, F. (2007) Exploring the ecological status of human altered streams through Generative Topographic Mapping. Environmental Modelling & Software, 22(7), 1053-1065. (download).
Spate, J., Gibert, K., Sànchez-Marrè, M., Frank, E., Comas, J., Athanasiadis, I., and Vellido, A. (2006) Data Mining as a Tool for Analysing Environmental Systems. Learning'06 International Conference. 'Between Learning and Data Mining' special session, 3rd of October, Vilanova i la Geltrú, Spain.
Etchells, T.A., Vellido, A., Martí, E., Lisboa, P.J.G., and Comas, J. (2006) On the prediction of the ecological status of human-altered streams and its rule-based interpretation. 3rd Biennial meeting of the International Environmental Modelling and Software Society, iEMSs'2006. Data Mining Workshop.
Vellido, A., Comas, J., Cruz, R., and Martí, E. (2006) Finding relevant features for the characterization of the ecological status of human altered streams using a constrained mixture model. 3rd Biennial meeting of the International Environmental Modelling and Software Society, iEMSs'2006. Data Mining Workshop.
Vicente, D., Vellido, A., Martí, E., Comas, J., and Rodriguez-Roda, I. (2004), “Exploration of the ecological status of Mediterranean rivers: Clustering, visualizing and reconstructing streams data using Generative Topographic Mapping”. In W.I.T. Transactions on Information and Communication Technologies, Vol.33, 121-130.
Vellido, A., Olier, I., Martí, E., Comas, J., and Rodríguez-Roda, I. (2004) STREAMES project: Exploration of the ecological status of Mediterranean rivers using Generative Topographic Mapping. Poster presentation at BESAI 2004 - 4th ECAI Workshop on Binding Environmental Sciences and Artificial Intelligence. August 2004, Valencia, Spain.
E-learning applications
Vellido,
A., Castro, F., Nebot, A. (2010) Clustering Educational Data.
In Romero, C., Ventura, S., Pechenizkiy, M., Baker, R.S.J.d.
(eds.) Handbook of
Educational data Mining, CRC Press, Taylor &
Francis Group, pp.75-92.
Castro,
F., Vellido, A., Nebot, À., and Minguillón, J. (2008)
Detección de Estudiantes con Comportamiento Atípico en
Entornos de Aprendizaje e-Learning. In Llamas-Nistal, M., Vaz
de Carvalho, C., and Rueda Artunduaga, C. (eds.) TICAI2006:
TICs para el Aprendizaje de la Ingeniería, pp.23-30.
IEEE, Sociedad de Educación: Capítulos Español, Portugués y
Colombiano.
Castro, F., Vellido, A., Nebot, A., Mugica, F. (2007) Applying Data Mining Techniques to e-Learning Problems. In: Jain, L.C., Tedman, R. and Tedman, D. (eds.) Evolution of Teaching and Learning Paradigms in Intelligent Environment. Studies in Computational Intelligence, Vol.62, Springer-Verlag, 183-221.
Vellido, A., Castro, F., Etchells, T.A., Nebot, A., and Mugica, F. (2007) Data Mining of Virtual Campus Data. In: Jain, L.C., Tedman, R. and Tedman, D. (eds.) Evolution of Teaching and Learning Paradigms in Intelligent Environment. Studies in Computational Intelligence, Vol.62, Springer-Verlag, 223-254.
Etchells,T.A., Nebot, A., Vellido, A., Lisboa, P.J.G., and Múgica, F. (2006) Learning what is important: feature selection and rule extraction in a virtual course. In Proceedings of the 14th European Symposium on Artificial Neural Networks, ESANN 2006, Bruges, Belgium, 401-406.
Vellido, A., Castro, F., Nebot, A., and Múgica, F., (2006) Characterization of atypical virtual campus usage behavior through robust generative relevance analysis, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.183-188.
Nebot, A., Castro, F., Múgica, F., and Vellido, A., (2006) Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79. [Shortlisted for The Fifth International Competition of Ph.D. Students in the WBE Area]
Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Detecting atypical student behaviour on an e-learning system, Accepted for oral presentation: VI Congreso Nacional de Informática Educativa; Simposio Nacional de Tecnologías de la Información y las Comunicaciones en la Educación, SINTICE’2005 (ADIE), Granada, Spain, September 2005.
Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Finding relevant features to characterize student behavior on an e-learning system, In: International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS 2005), Las Vegas, Nevada, USA, June 2005.
Neuroscience applications
Ortega-Martorell, S., Olier, I., Vellido, A., Lisboa, P.J.G., El-Deredy, W. (2011) Comparing independent component analysis and non-negative matrix factorisation in the identification of event-related brain dynamics, 11th International Conference on Cognitive Neuroscience (ICON XI), Abstract A066, p.82.
Olier,
I.,
Amengual, J. and Vellido, A. (2011) A variational Bayesian
approach for the robust estimation of cortical silent periods
from EMG time series of brain stroke patients. Neurocomputing,
74(9): 1301-1314.
Olier,
I.,
Amengual, J., Vellido, A. (2010) Segmentation of EMG time series using a
variational Bayesian approach for the robust estimation of
cortical silent periods. 18th European Symposiun on Artificial
Neural Networks (ESANN
2010), 439-444.
Vellido, A., El-Deredy, W., and Lisboa, P.J.G. (2004) Studying embedded human EEG dynamics using Generative Topographic Mapping . Technical Report LSI-04-8-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A., and El-Deredy, W. (2004) Exploring dopamine-mediated reward processing through the analysis of EEG-measured gamma-band brain oscillations. Technical Report LSI-04-7-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
Vellido, A., El-Deredy, W., Gruber, T., Zald, D.H., McGlone, F.P., and Müller, M.M. (2003) Reward predictability and oscillatory brain processes. In The Annual Computational Neuroscience Meeting, CNS'2003. Poster presentation. Alicante, Spain.
Miscellanea
I.
Paz, À. Nebot,
E. Romero, F. Mugica and A. Vellido (2016) A
methodological approach for algorithmic composition
systems' parameter spaces aesthetic exploration, In 2016 IEEE
Congress on Evolutionary
Computation (CEC / WCCI'16),
pp.1317-1323.
E. Racec, S. Budulan, and A. Vellido (2016) Computational Intelligence in architectural and interior design: a state-of-the-art and outlook on the field. In Artificial Intelligence Research and Development: Proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2016), Barcelona, Spain, Vol. 288, p.108. IOS Press. [draft]
Poveda, J. and Vellido, A. (2006) Neural Network Models for Language Acquisition: A Brief Survey. In Proc. of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006), Burgos, Spain. LNCS Vol.4224, 1346-1357.
Vicente, D. and Vellido, A. (2004) Review of Hierarchical Models for Data Clustering and Visualization. In R.Giráldez, J.C. Riquelme, J.S. Aguilar-Ruiz (Eds.) Tendencias de la Minería de Datos en España. Red Española de Minería de Datos.
Alquézar, R., Belanche, L., Nebot, A., Romero, E., and Vellido, A. (2004) Investigación actual del grupo SOCO: Metodologías híbridas de Soft Computing. In R.Giráldez, J.C. Riquelme, J.S. Aguilar-Ruiz (Eds.) Tendencias de la Minería de Datos en España. Red Española de Minería de Datos.
Last updated 25/01/19