Alfredo Vellido

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Using random forests for assistance in the curation of G-protein coupled receptor databases

Aleksei Shkurin, Alfredo Vellido, 2017, Biomedical engineering online.

Misclassification of class C G-protein-coupled receptors as a label noise problem

Alfredo Vellido, René Alquézar, Caroline König, 2014, ESANN.

DSS-oriented exploration of a multi-centre magnetic resonance spectroscopy brain tumour dataset through visualization

Margarida Julià-Sapé, Alfredo Vellido, Enrique Romero, 2008, ESANN.

Brain Tumor Pathological Area Delimitation through Non-negative Matrix Factorization

Paulo J. G. Lisboa, Margarida Julià-Sapé, Carles Arús, 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

Severe sepsis mortality prediction with logistic regression over latent factors

Alfredo Vellido, Vicent J. Ribas, Juan Carlos Ruiz-Rodríguez, 2012, Expert Syst. Appl..

Outlier exploration and diagnostic classification of a multi-centre 1H-MRS brain tumour database

Lluís A. Belanche Muñoz, Félix Fernando González-Navarro, Margarida Julià-Sapé, 2009, Neurocomputing.

Advances in machine learning and computational intelligence

Michael Biehl, Frank-Michael Schleif, Alfredo Vellido, 2009, Neurocomputing.

A quotient basis kernel for the prediction of mortality in severe sepsis patients

Enrique Romero, Alfredo Vellido, Vicent J. Ribas, 2013, ESANN.

The influence of alignment-free sequence representations on the semi-supervised classification of class C G protein-coupled receptors

Alfredo Vellido, Raúl Cruz-Barbosa, Jesús Giraldo, 2014, Medical & Biological Engineering & Computing.

A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases

Margarida Julià-Sapé, Carles Arús, Alfredo Vellido, 2016, ESANN.

Visual interpretation of class C GPCR subtype overlapping from the nonlinear mapping of transformed primary sequences

Alfredo Vellido, Jesús Giraldo, Martha Ivón Cárdenas, 2014, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

Identification of fuzzy models to predict students performance in an e-learning environment

Àngela Nebot, Francisco Mugica, Alfredo Vellido, 2006 .

Binary classification of brain tumours using a Discrete Wavelet Transform and energy criteria

Alfredo Vellido, Enrique Romero, Carlos Arizmendi, 2011, 2011 IEEE Second Latin American Symposium on Circuits and Systems (LASCAS).

Robust analysis of MRS brain tumour data using t-GTM

Paulo J. G. Lisboa, Alfredo Vellido, Dolores Vicente, 2006, Neurocomputing.

Computational Intelligence in Interior Design: State-of-the-Art and Outlook

Alfredo Vellido, Emil Racec, Stefania Budulan, 2016, CCIA.

Feature and model selection with discriminatory visualization for diagnostic classification of brain tumors

Lluís A. Belanche Muñoz, Félix Fernando González-Navarro, Margarida Julià-Sapé, 2010, Neurocomputing.

Corrigendum to "Severe sepsis mortality prediction with logistic regression over latent factors" [Expert Systems with Applications 39 (2) (2012) 1937-1943]

Alfredo Vellido, Vicent J. Ribas, Juan Carlos Ruiz-Rodríguez, 2012, Expert Syst. Appl..

The extracellular N-terminal domain suffices to discriminate class C G Protein-Coupled Receptor subtypes from n-grams of their sequences

Alfredo Vellido, René Alquézar, Caroline König, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Blood Pressure Assessment with Differential Pulse Transit Time and Deep Learning: A Proof of Concept

Alfredo Vellido, Vicent Ribas Ripoll, A. Vellido, 2018, Kidney Diseases.

Diagnosis of brain tumours from magnetic resonance spectroscopy using wavelets and Neural Networks

Francisco del Pozo, Alfredo Vellido, Enrique Romero, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

Visual characterization of misclassified Class C GPCRs through Manifold-based machine learning methods

Alfredo Vellido, René Alquézar, Caroline König, 2015 .

Bioinformatics and medicine in the era of deep learning pdf

Paulo J. G. Lisboa, Davide Bacciu, Ruxandra Stoean, 2018, ESANN.

A MAP approach for convex non-negative matrix factorization in the diagnosis of brain tumors

Lluís A. Belanche Muñoz, Alfredo Vellido, Albert Vilamala, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

Describing Customer Loyalty to Spanish Petrol Stations Through Rule Extraction

Àngela Nebot, Alfredo Vellido, Terence A. Etchells, 2006, IDEAL.

Computational Intelligence Methods for Bioinformatics and Biostatistics: 8th International Meeting, CIBB 2011, Gargnano del Garda, Italy, June 30 - ...

Roberto Tagliaferri, Alfredo Vellido, Elia Biganzoli, 2012, CIBB 2012.

The effect of noise and sample size on an unsupervised feature selection method for manifold learning

Alfredo Vellido, Jorge S. Velazco, A. Vellido, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Two-Stage Clustering of a Human Brain Tumour Dataset using Manifold Learning Models

Alfredo Vellido, Raúl Cruz-Barbosa, A. Vellido, 2008, BIOSIGNALS.

Making nonlinear manifold learning models interpretable: The manifold grand tour

Paulo J. G. Lisboa, José David Martín-Guerrero, Alfredo Vellido, 2015, Expert Syst. Appl..

A Weighted Cramér's V Index for the Assessment of Stability in the Fuzzy Clustering of Class C G Protein-Coupled Receptors

Àngela Nebot, Alfredo Vellido, Christiana Halka, 2015, IWBBIO.

Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis

Margarida Julià-Sapé, Carles Arús, Alfredo Vellido, 2010, ESANN.

Pattern recognition methods for MRS analysis and classification

Paulo J. G. Lisboa, Alfredo Vellido, S.P.J. Kirby, 1997 .

Determination of feature relevance for the grouping of motor unit action potentials through a generative mixture model

Alfredo Vellido, Adriano de Oliveira Andrade, A. Vellido, 2007, Biomed. Signal Process. Control..

Unfolding the Manifold in Generative Topographic Mapping

Alfredo Vellido, Raúl Cruz-Barbosa, 2008, HAIS.

Variational Bayesian Generative Topographic Mapping

Alfredo Vellido, Iván Olier, A. Vellido, 2008, J. Math. Model. Algorithms.

Advances in clustering and visualization of time series using GTM through time

Alfredo Vellido, Iván Olier, A. Vellido, 2008, Neural Networks.

Segmenting the e-Commerce Market Using the Generative Topographic Mapping

Paulo J. G. Lisboa, Alfredo Vellido, Karon Meehan, 2000, MICAI.

Machine learning in critical care: state-of-the-art and a sepsis case study

Alfredo Vellido, Vicent Ribas, Carles Morales, 2018, BioMedical Engineering OnLine.

Metrics for Probabilistic Geometries

Neil D. Lawrence, Søren Hauberg, Alfredo Vellido, 2014, UAI.

Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours

Paulo J. G. Lisboa, Margarida Julià-Sapé, Carles Arús, 2012, BMC Bioinformatics.

Learning what is important: feature selection and rule extraction in a virtual course

Paulo J. G. Lisboa, Àngela Nebot, Francisco Mugica, 2006, ESANN.

Sepsis mortality prediction with the Quotient Basis Kernel

Alfredo Vellido, Enrique Romero, Vicent J. Ribas, 2014, Artif. Intell. Medicine.

Semi-supervised Outcome Prediction for a Type of Human Brain Tumour Using Partially Labeled MRS Information

Alfredo Vellido, Raúl Cruz-Barbosa, 2009, IDEAL.

On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statins

Alfredo Vellido, Vicent J. Ribas, Juan Carlos Ruiz-Rodríguez, 2011, CIBB.

Rule-Based Assistance to Brain Tumour Diagnosis Using LR-FIR

Àngela Nebot, Margarida Julià-Sapé, Carles Arús, 2008, KES.

Discriminant Convex Non-negative Matrix Factorization for the classification of human brain tumours

Paulo J. G. Lisboa, Alfredo Vellido, Sandra Ortega-Martorell, 2013, Pattern Recognit. Lett..

Characterization of atypical virtual campus usage behavior through robust generative relevance analysis

Àngela Nebot, Francisco Mugica, Alfredo Vellido, 2006 .

On the prediction of the ecological status of human-altered streams and its rule-based interpretation

Paulo J. G. Lisboa, Alfredo Vellido, Terence A. Etchells, 2006 .

Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree

Alfredo Vellido, Jesús Giraldo, Iván Olier, 2011, CIBB.

Variational GTM

Alfredo Vellido, Iván Olier, A. Vellido, 2007, IDEAL.

Outstanding Issues for Clinical Decision Support with Neural Networks

Paulo J. G. Lisboa, Alfredo Vellido, Helen Wong, 2000, ANNIMAB.

On the Improvement of the Mapping Trustworthiness and Continuity of a Manifold Learning Model

Alfredo Vellido, Raúl Cruz-Barbosa, 2008, IDEAL.

Cartogram visualization for nonlinear manifold learning models

Àngela Nebot, Alfredo Vellido, David L. García, 2012, Data Mining and Knowledge Discovery.

A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences

Alfredo Vellido, Jesús Giraldo, Iván Olier, 2011, ESANN.

A variational formulation for GTM through time

Alfredo Vellido, Iván Olier, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Leveraging Data Science for a Personalized Haemodialysis

Karina Gibert, Alfredo Vellido, Miguel Hueso, 2020, Kidney Diseases.

Using machine learning tools for protein database biocuration assistance

Alfredo Vellido, René Alquézar, Caroline König, 2018, Scientific Reports.

Physics and Machine Learning: Emerging Paradigms

Paulo J. G. Lisboa, José David Martín-Guerrero, Alfredo Vellido, 2016, ESANN.

A methodology for the characterization of business-to-consumer E-commerce

Alfredo Vellido, A. Vellido, 2000 .

Frequency Selection for the Diagnostic Characterization of Human Brain Tumours

Enrique Romero, Alfredo Vellido, Carlos Arizmendi, 2009, CCIA.

Missing data imputation through GTM as a mixture of t-distributions

Alfredo Vellido, A. Vellido, 2006, Neural Networks.

The importance of interpretability and visualization in machine learning for applications in medicine and health care

Alfredo Vellido, A. Vellido, 2019, Neural Computing and Applications.

Random Forests for Quality Control in G-Protein Coupled Receptor Databases

Aleksei Shkurin, Alfredo Vellido, A. Vellido, 2016, IWBBIO.

Selective smoothing of the generative topographic mapping

Paulo J. G. Lisboa, Alfredo Vellido, Wael El-Deredy, 2003, IEEE Trans. Neural Networks.

Finding Class C GPCR Subtype-Discriminating N-grams through Feature Selection

Alfredo Vellido, René Alquézar, Caroline König, 2014, PACBB.

Comparative Evaluation of Semi-supervised Geodesic GTM

Alfredo Vellido, Raúl Cruz-Barbosa, 2009, HAIS.

Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors

Alfredo Vellido, René Alquézar, Caroline König, 2015, BMC Bioinformatics.

Robust cartogram visualization of outliers in manifold learning

Alfredo Vellido, Alessandra Tosi, 2013, ESANN.

Neural Networks and Other Machine Learning Methods in Cancer Research

Paulo J. G. Lisboa, Alfredo Vellido, P. Lisboa, 2007, IWANN.

Geodesic Generative Topographic Mapping

Alfredo Vellido, Raúl Cruz-Barbosa, 2008, IBERAMIA.

Data Mining in Cancer Research [Application Notes]

Paulo J. G. Lisboa, Francesco Napolitano, José David Martín-Guerrero, 2010, IEEE Computational Intelligence Magazine.

Big Data Analytics for Obesity Prediction

Alfredo Vellido, Vicent J. Ribas, Ahsan Bilal, 2018, CCIA.

Quantitative Characterization and Prediction of On-Line Purchasing Behavior: A Latent Variable Approach

Paulo J. G. Lisboa, Alfredo Vellido, Karon Meehan, 2000, Int. J. Electron. Commer..

Automated Quality Control for Proton Magnetic Resonance Spectroscopy Data Using Convex Non-negative Matrix Factorization

Margarida Julià-Sapé, Carles Arús, Alfredo Vellido, 2016, IWBBIO.

Exploration Of The Ecological Status OfMediterranean Rivers: Clustering,Visualizing And Reconstructing Streams DataUsing Generative Topographic Mapping

Ignasi Rodríguez-Roda, Alfredo Vellido, J. Comas, 2004 .

Machine learning in cancer research: implications for personalised medicine

Paulo J. G. Lisboa, Alfredo Vellido, Elia Biganzoli, 2008, ESANN.

Spectral decomposition methods for the analysis of MRS information from human brain tumors

Paulo J. G. Lisboa, Margarida Julià-Sapé, Carles Arús, 2011, The 2011 International Joint Conference on Neural Networks.

Manifold learning visualization of Metabotropic Glutamate Receptors

Alfredo Vellido, Jesús Giraldo, Martha Ivón Cárdenas, 2014, CCIA.

On the Computation of the Geodesic Distance with an Application to Dimensionality Reduction in a Neuro-Oncology Problem

Alfredo Vellido, Raúl Cruz-Barbosa, David Bautista-Villavicencio, 2011, CIARP.

On the benefits for model regularization of a variational formulation of GTM

Alfredo Vellido, Iván Olier, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

On the use of decision trees for ICU outcome prediction in sepsis patients treated with statins

Alfredo Vellido, Vicent J. Ribas, Juan Carlos Ruiz-Rodríguez, 2011, 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

Intelligent data analysis approaches to churn as a business problem: a survey

Àngela Nebot, Alfredo Vellido, David L. García, 2017, Knowledge and Information Systems.

Societal Issues in Machine Learning: When Learning from Data is Not Enough

Paulo J. G. Lisboa, Davide Bacciu, Luca Oneto, 2019, ESANN.

A variational Bayesian approach for the robust analysis of the cortical silent period from EMG recordings of brain stroke patients

Alfredo Vellido, Iván Olier, Julià L. Amengual, 2011, Neurocomputing.

Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian Decomposition and Bayesian Neural Networks

Enrique Romero, Alfredo Vellido, Daniel A. Sierra, 2014, Expert Syst. Appl..

Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy

Alfredo Vellido, Anders Jonsson, Carlo Barbieri, 2018, Kidney Diseases.

Neural Network Models for Language Acquisition: A Brief Survey

Alfredo Vellido, Jordi Poveda, A. Vellido, 2006, IDEAL.

Topological Sequence Segments Discriminate Between Class C GPCR Subtypes

Alfredo Vellido, René Alquézar, Caroline König, 2017, PACBB.

Towards interpretable classifiers with blind signal separation

Paulo J. G. Lisboa, Enrique Romero, José David Martín-Guerrero, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Making machine learning models interpretable

Paulo J. G. Lisboa, José David Martín-Guerrero, Alfredo Vellido, 2012, ESANN.

SVM-Based Classification of Class C GPCRs from Alignment-Free Physicochemical Transformations of Their Sequences

Alfredo Vellido, René Alquézar, Caroline König, 2013, ICIAP Workshops.

Discovering Subtype Specific n-Gram Motifs in Class C GPCR N-Termini

Alfredo Vellido, René Alquézar, Caroline König, 2017, CCIA.

Comparative Diagnostic Accuracy of Linear and Nonlinear Feature Extraction Methods in a Neuro-oncology Problem

Alfredo Vellido, Raúl Cruz-Barbosa, David Bautista-Villavicencio, 2011, MCPR.

Advances in Semi-Supervised Alignment-Free Classication of G Protein-Coupled Receptors

Alfredo Vellido, Raúl Cruz-Barbosa, Jesús Giraldo, 2013, IWBBIO.

Preprocessing MRS Information for Classification of Human Brain Tumours

Alfredo Vellido, Carlos Arizmendi, Enrique Romero, 2012 .

Visualizing pay-per-view television customers churn using cartograms and flow maps

Àngela Nebot, Alfredo Vellido, David L. García, 2013, ESANN.

Assessment of the Effect of Noise on an Unsupervised Feature Selection Method for Generative Topographic Mapping

Alfredo Vellido, Jorge S. Velazco, 2008, ICEIS.

Data Mining of Virtual Campus Data

Àngela Nebot, Francisco Mugica, Alfredo Vellido, 2007 .

Comparative Assessment of the Robustness of Missing Data Imputation Through Generative Topographic Mapping

Alfredo Vellido, Iván Olier, 2005, IWANN.

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization - Proceedings of the 13th International Workshop, WSOM+ 2019, Barcelona, Spain, June 26-28, 2019

Alfredo Vellido, 2020, WSOM+.

Clustering and Visualization of Multivariate Time Series

Alfredo Vellido, Iván Olier, A. Vellido, 2010 .

On the Influence of Class Information in the Two-Stage Clustering of a Human Brain Tumour Dataset

Alfredo Vellido, Raúl Cruz-Barbosa, 2007, MICAI.

A decision making support tool: The resilience management fuzzy controller

Àngela Nebot, Francisco Mugica, Alfredo Vellido, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns

Alfredo Vellido, René Alquézar, Caroline König, 2014, J. Integr. Bioinform..

Exploratory Characterization of Outliers in a Multi-centre 1H-MRS Brain Tumour Dataset

Margarida Julià-Sapé, Carles Arús, Alfredo Vellido, 2008, KES.

Functional topographic mapping for robust handling of outliers in brain tumour data

Paulo J. G. Lisboa, Alfredo Vellido, 2005, ESANN.

Exploring the ecological status of human altered streams through Generative Topographic Mapping

Ignasi Rodríguez-Roda, Alfredo Vellido, Joaquim Comas, 2007, Environ. Model. Softw..

Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping

Alfredo Vellido, A. Vellido, 2006, ICANN.

Neural networks in practice-an example from magnetic resonance spectroscopy

Paulo J. G. Lisboa, Alfredo Vellido, Wael El-Deredy, 1998 .

Interpreting response to TMZ therapy in murine GL261 glioblastoma by combining Radiomics, Convex-NMF and feature selection in MRI/MRSI data analysis

Margarida Julià-Sapé, Alfredo Vellido, Enrique Romero, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Tissue characterisation with NMR spectroscopy: current state and future prospects for the application of neural networks analysis

Paulo J. G. Lisboa, Alfredo Vellido, Wael El-Deredy, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods

Alfredo Vellido, Iván Olier, Julià L. Amengual, 2010, ESANN.

Feature Selection with Single-Layer Perceptrons for a Multicentre 1H-MRS Brain Tumour Database

Josep M. Sopena, Enrique Romero, Alfredo Vellido, 2009, IWANN.

Applying Data Mining Techniques to e-Learning Problems

Àngela Nebot, Francisco Mugica, Alfredo Vellido, 2007 .

Visual Exploratory Assessment of Class C GPCR Extracellular Domains Discrimination Capabilities

Alfredo Vellido, Jesús Giraldo, Martha Ivón Cárdenas, 2016, PACBB.

Discovering Hidden Pathways in Bioinformatics

Paulo J. G. Lisboa, Davide Bacciu, Jonathan M. Garibaldi, 2011, CIBB.

A methodological approach for algorithmic composition systems' parameter spaces aesthetic exploration

Àngela Nebot, Francisco Mugica, Alfredo Vellido, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Neural networks in business: a survey of applications (1992–1998)

Alfredo Vellido, A. Vellido, 1999 .

Neural Networks for B2C E-Commerce Analysis: Some Elements of Best Practice

Alfredo Vellido, 2002, ICEIS.

Cartogram-Based Data Visualization Using the Growing Hierarchical SOM

Alfredo Vellido, Àngela Martín, 2013, CCIA.

Exploratory Visualization of Misclassified GPCRs from their transformed unaligned sequences using manifold learning techniques

Alfredo Vellido, René Alquézar, Caroline König, 2014, IWBBIO.

On the improvement of brain tumour data clustering using class information

Alfredo Vellido, Raúl Cruz-Barbosa, 2006, STAIRS.

Semi-Supervised Analysis of Human Brain Tumours from Partially Labeled MRS Information, Using Manifold Learning Models

Alfredo Vellido, Raúl Cruz-Barbosa, A. Vellido, 2011, Int. J. Neural Syst..

Handling outliers and missing data in brain tumour clinical assessment using t-GTM

Paulo J. G. Lisboa, Alfredo Vellido, Dolores Vicente, 2005, ESANN.

Applying Conditional Independence Maps to Improve Sepsis Prognosis

Alfredo Vellido, Vicent J. Ribas, Carles Morales, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

Machine Learning for Clinical Decision-Making: Challenges and Opportunities

Emilia Gómez, Maja Cikes, Miguel Ángel González Ballester, 2019 .

Classification of human brain tumours from MRS data using Discrete Wavelet Transform and Bayesian Neural Networks

Alfredo Vellido, Enrique Romero, Carlos Arizmendi, 2012, Expert Syst. Appl..

On the Initialization of Two-Stage Clustering with Class-GTM

Alfredo Vellido, Raúl Cruz-Barbosa, 2007, CAEPIA.

Bias reduction in skewed binary classification with Bayesian neural networks

Paulo J. G. Lisboa, Alfredo Vellido, H. Wong, 2000, Neural Networks.

Machine Learning for Critical Care: An Overview and a Sepsis Case Study

Alfredo Vellido, Vicent J. Ribas, Juan Carlos Ruiz-Rodríguez, 2017, IWBBIO.

Aprendizaje generativo de variedades para la exploración de datos parcialmente etiquetados

Alfredo Vellido, Raúl Cruz-Barbosa, 2013, Computación y Sistemas.

Kernel generative topographic mapping

Alfredo Vellido, Jesús Giraldo, Iván Olier, 2010, ESANN.

Cartogram representation of the batch-SOM magnification factor

Alfredo Vellido, Alessandra Tosi, 2012, ESANN.

Telecommunications Customers Churn Monitoring using Flow Maps and Cartogram Visualization

Àngela Nebot, Alfredo Vellido, David L. García, 2016, GRAPP/IVAPP.

Handling outliers in brain tumour MRS data analysis through robust topographic mapping

Paulo J. G. Lisboa, Alfredo Vellido, P. Lisboa, 2006, Comput. Biol. Medicine.

Bayesian semi non-negative matrix factorisation

Alfredo Vellido, Albert Vilamala, Lluís A. Belanche, 2016, ESANN.

An Electronic Commerce Application of the Bayesian Framework for MLPs: The Effect of Marginalisation and ARD

Paulo J. G. Lisboa, Alfredo Vellido, 2001, Neural Computing & Applications.

Semi-supervised geodesic Generative Topographic Mapping

Alfredo Vellido, Raúl Cruz-Barbosa, A. Vellido, 2010, Pattern Recognit. Lett..

Classification, Dimensionality Reduction, and Maximally Discriminatory Visualization of a Multicentre 1H-MRS Database of Brain Tumors

Paulo J. G. Lisboa, Margarida Julià-Sapé, Carles Arús, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

Network Community Cluster-Based Analysis for the Identification of Potential Leukemia Drug Targets

Alfredo Vellido, Adrián Bazaga, A. Vellido, 2019, WSOM+.

Severe sepsis mortality prediction with relevance vector machines

Alfredo Vellido, Vicent J. Ribas, Juan Carlos Ruiz-Rodríguez, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Extraction of artefactual MRS patterns from a large database using non‐negative matrix factorization

Margarida Julià-Sapé, Carles Arús, Alfredo Vellido, 2019, NMR in biomedicine.

The generative topographic mapping as a principal model for data visualization and market segmentation: an electronic commerce case

Paulo J. G. Lisboa, Alfredo Vellido, Karon Meehan, 2000, Int. J. Comput. Syst. Signals.

Probability Ridges and Distortion Flows: Visualizing Multivariate Time Series Using a Variational Bayesian Manifold Learning Method

Alfredo Vellido, Iván Olier, Alessandra Tosi, 2014, WSOM.

Brain tumour classification using Gaussian decomposition and neural networks

Enrique Romero, Alfredo Vellido, Daniel A. Sierra, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Electricity Rate Planning for the Current Consumer Market Scenario Through Segmentation of Consumption Time Series

Alfredo Vellido, David L. García, 2017, EPIA.

Seeing is believing: The importance of visualization in real-world machine learning applications

Paulo J. G. Lisboa, José David Martín-Guerrero, Alfredo Vellido, 2011, ESANN.

Segmentation of the on-line shopping market using neural networks

Paulo J. G. Lisboa, Alfredo Vellido, Karon Meehan, 1999 .

Neurocomputing Research Developments

Tommy W. S. Chow, Lokendra Shastri, James A. Reggia, 2007 .

Finding Relevant Features to Characterize Student Behavior on an e-Learning System

Àngela Nebot, Julià Minguillón, Alfredo Vellido, 2005, FECS.

Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns.

Alfredo Vellido, René Alquézar, Caroline König, 2014, Journal of integrative bioinformatics.

Computational Intelligence in biomedicine: Some contributions

Paulo J. G. Lisboa, José David Martín-Guerrero, Alfredo Vellido, 2010, ESANN.

Classifying malignant brain tumours from 1H-MRS data using Breadth Ensemble Learning

Lluís A. Belanche Muñoz, Alfredo Vellido, Albert Vilamala, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

The Coming of Age of Interpretable and Explainable Machine Learning Models

Paulo J. G. Lisboa, Thomas Villmann, Alfredo Vellido, 2023, ESANN.

Visual Mining of Industrial Gas Turbines Sensor Data as an Industry 4.0 Application

Karina Gibert, Alfredo Vellido, Angel X. Astudillo Aguilar, 2021, SOCO.

Survival of breast cancer patients following surgery: a detailed assessment of the multi-layer perceptron and Cox's proportional hazard model

Paulo J. G. Lisboa, Alfredo Vellido, S.P.J. Kirby, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Convex Non-Negative Matrix Factorization for Brain Tumor Delimitation from MRSI Data

Paulo J. G. Lisboa, Margarida Julià-Sapé, Carles Arús, 2012, PloS one.

Characterising and Segmenting the Business-to-Consumer E-Commerce Market Using Neural Networks

Paulo J. G. Lisboa, Alfredo Vellido, Karon Meehan, 2000 .

Societal Issues Concerning the Application of Artificial Intelligence in Medicine

Alfredo Vellido, A. Vellido, 2018, Kidney Diseases.

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

Paulo J. G. Lisboa, Enrique Romero, Margarida Julià-Sapé, 2013, PloS one.

Systematic Analysis of Primary Sequence Domain Segments for the Discrimination Between Class C GPCR Subtypes

Alfredo Vellido, René Alquézar, Caroline König, 2018, Interdisciplinary Sciences: Computational Life Sciences.