Alfredo Vellido 个人学术档案

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	总计	2019 年至今
引用	5299	2182
h 指数	35	21
i10 指数	81	34

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Margarida Julià-SapéUniversitat Autònoma de Barcelona (UAB)在 uab.cat 的电子邮件经过验证
Angela NebotUniversitat Politècnica de Catalunya, Dept. Computer Science, Research group: Soft Computing (SOCO)在 cs.upc.edu 的电子邮件经过验证
Vicent Ribas RipollEurecat在 ieee.org 的电子邮件经过验证
Ivan OlierReader in Artificial Intelligence and Data Science, Liverpool John Moores University在 ljmu.ac.uk 的电子邮件经过验证
Jesús GiraldoProfesor de Bioestadística (UAB)在 uab.es 的电子邮件经过验证
Félix Castro CITIS-UAEH在 lsi.upc.edu 的电子邮件经过验证
Sandra Ortega-MartorellReader in Data Science, Liverpool John Moores University在 ljmu.ac.uk 的电子邮件经过验证
René AlquézarUniversitat Politecnica de Catalunya在 cs.upc.edu 的电子邮件经过验证
CARLOS JULIO ARIZMENDI PEREIRAUniversidad autonoma de bucaramanga在 unab.edu.co 的电子邮件经过验证
Enrique RomeroDirector of Research Universitat Politècnica de Catalunya, Researcher at CIMNE在 upc.edu 的电子邮件经过验证
Wael El-DeredyUniversidad de Valparaiso, Chile在 UV.CL 的电子邮件经过验证
Lluís A. BelancheAssociate Professor. Dept. of Computer Science, Technical University of Catalonia在 cs.upc.edu 的电子邮件经过验证
Alessandra TosiPostdoctoral Researcher, University of Oxford在 lsi.upc.edu 的电子邮件经过验证
Elia Mario BiganzoliProfessor of Medical Statistics, University of Milano在 unimi.it 的电子邮件经过验证
Rui V Simoesi3S - Institute for Research and Innovation in Health在 i3s.up.pt 的电子邮件经过验证
Julià Minguillón (0000-0002-0080-846...Universitat Oberta de Catalunya (UOC)在 uoc.edu 的电子邮件经过验证
Albert VilamalaDTU在 dtu.dk 的电子邮件经过验证
Davide BacciuDipartimento di Informatica, Università di Pisa在 di.unipi.it 的电子邮件经过验证
Félix Fernando González-NavarroUniversidad Autónoma de Baja California在 uabc.edu.mx 的电子邮件经过验证
Michele CeccarelliUniversity of Miami在 miami.edu 的电子邮件经过验证

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Alfredo Vellido

Full Professor in Artificial Intelligence, Universitat Politècnica de Catalunya (UPC

在 cs.upc.edu 的电子邮件经过验证 - 首页

Medical Applications of ML Bioinformatics Data Visualization Statistical ML Explainable ML


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
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	638	1999
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	511	2007
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	484	2020
Making machine learning models interpretable. A Vellido, JD Martín-Guerrero, PJG Lisboa ESANN 12, 163-172, 2012	423*	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	225	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	104	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	101	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
Metrics for probabilistic geometries A Tosi, S Hauberg, A Vellido, ND Lawrence arXiv preprint arXiv:1411.7432, 2014	69	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	63	2018
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
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	61	2023
Clustering educational data A Vellido, F Castro, A Nebot Handbook of educational data mining, 75-92, 2010	61	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	59*	2022
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	59	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	58	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

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