Neural networks in business: a survey of applications (1992–1998) A Vellido, PJG Lisboa, J Vaughan Expert Systems with applications 17 (1), 51-70, 1999 | 643 | 1999 |
The importance of interpretability and visualization in machine learning for applications in medicine and health care A Vellido Neural computing and applications 32 (24), 18069-18083, 2020 | 513 | 2020 |
Applying data mining techniques to e-learning problems F Castro, A Vellido, A Nebot, F Mugica Evolution of teaching and learning paradigms in intelligent environment, 183-221, 2007 | 513 | 2007 |
Making machine learning models interpretable. A Vellido, JD Martín-Guerrero, PJG Lisboa ESANN 12, 163-172, 2012 | 429* | 2012 |
Segmentation of the on-line shopping market using neural networks A Vellido, PJG Lisboa, K Meehan Expert systems with applications 17 (4), 303-314, 1999 | 227 | 1999 |
Quantitative characterization and prediction of on-line purchasing behavior: A latent variable approach A Vellido, PJG Lisboa, K Meehan International journal of electronic commerce 4 (4), 83-104, 2000 | 191 | 2000 |
Societal issues concerning the application of artificial intelligence in medicine A Vellido Kidney Diseases 5 (1), 11-17, 2019 | 109 | 2019 |
Intelligent data analysis approaches to churn as a business problem: a survey DL García, À Nebot, A Vellido Knowledge and Information Systems 51 (3), 719-774, 2017 | 106 | 2017 |
Business applications of neural networks: the state-of-the-art of real-world applications PJG Lisboa, B Edisbury, A Vellido World scientific, 2000 | 95 | 2000 |
The coming of age of interpretable and explainable machine learning models PJG Lisboa, S Saralajew, A Vellido, R Fernández-Domenech, T Villmann Neurocomputing 535, 25-39, 2023 | 79 | 2023 |
Metrics for probabilistic geometries A Tosi, S Hauberg, A Vellido, ND Lawrence arXiv preprint arXiv:1411.7432, 2014 | 71 | 2014 |
Machine learning in critical care: state-of-the-art and a sepsis case study A Vellido, V Ribas, C Morales, A Ruiz Sanmartín, JC Ruiz Rodríguez Biomedical engineering online 17, 1-18, 2018 | 64 | 2018 |
Clustering educational data A Vellido, F Castro, A Nebot Handbook of educational data mining, 75-92, 2010 | 64 | 2010 |
Machine learning for clinical decision-making: challenges and opportunities in cardiovascular imaging S Sanchez-Martinez, O Camara, G Piella, M Cikes, ... Frontiers in cardiovascular medicine 8, 765693, 2022 | 62* | 2022 |
Data mining in cancer research [application notes] PJG Lisboa, A Vellido, R Tagliaferri, F Napolitano, M Ceccarelli, ... IEEE computational intelligence magazine 5 (1), 14-18, 2010 | 62 | 2010 |
Severe sepsis mortality prediction with relevance vector machines VJ Ribas, JC López, A Ruiz-Sanmartín, JC Ruiz-Rodríguez, J Rello, ... 2011 annual international conference of the IEEE engineering in medicine and …, 2011 | 60 | 2011 |
Classification of human brain tumours from MRS data using Discrete Wavelet Transform and Bayesian Neural Networks C Arizmendi, A Vellido, E Romero Expert Systems with Applications 39 (5), 5223-5232, 2012 | 59 | 2012 |
Seeing is believing: The importance of visualization in real-world machine learning applications A Vellido Alcacena, JD Martín, F Rossi, PJG Lisboa Proceedings: 19th European Symposium on Artificial Neural Networks …, 2011 | 56 | 2011 |
Missing data imputation through GTM as a mixture of t-distributions A Vellido Neural Networks 19 (10), 1624-1635, 2006 | 52 | 2006 |
Convex non-negative matrix factorization for brain tumor delimitation from MRSI data S Ortega-Martorell, PJG Lisboa, A Vellido, RV Simões, M Pumarola, ... Public Library of Science 7 (10), e47824, 2012 | 51 | 2012 |