Computación evolutiva basada en un modelo de codificación implícita. - Francisco J. Veredas 001; Francisco J. Vico (Inteligencia Artif., 1998)

Automatic design synthesis with artificial intelligence techniques. - Francisco J. Vico; Francisco J. Veredas 001; José Manuel Bravo; J. Almaraz (Artif. Intell. Eng., 1999)

Inhibitory unlearning: a mechanism for increasing the storage capacity in an attractor network. - O. R. Manzano; Francisco J. Veredas 001; M. J. Guillén; Francisco J. Vico; J. Román (KES, 2000)

Animal-like adaptive behavior. - Francisco J. Vico; P. Mir; Francisco J. Veredas 001; J. de La Torre (Artif. Intell. Eng., 2001)

A Competitive-Based Method for Determining the Number of Groups: A Clinical Application. - Antonio Sánchez; Francisco J. Vico; Santiago Cabello; Francisco J. Veredas 001; Yamina Seamari; Isaac López; Javier Farfán; Guillermo García-Herrera (IWANN, 2005)

Estudio de la influencia de factores fisiologicos y de conectividad de red en la correlacion de actividad entre pares de neuronas de integracion y disparo. - Francisco J. Veredas 001; Francisco J. Vico; José M. Alonso (Inteligencia Artif., 2005)

Optimized synaptic conductance model for integrate-and-fire neurons. - Francisco J. Veredas 001; Héctor Mesa (Artificial Intelligence and Soft Computing, 2006)

Evolving networks of integrate-and-fire neurons. - Francisco J. Veredas 001; Francisco J. Vico; José M. Alonso (Neurocomputing, 2006)

Integrate-and-Fire Neural Networks with Monosynaptic-Like Correlated Activity. - Héctor Mesa; Francisco J. Veredas 001 (ICANN (1), 2007)

Self-organizing Maps of Spiking Neurons with Reduced Precision of Correlated Firing. - Francisco J. Veredas 001; Luis A. Martínez; Héctor Mesa (ICANN (2), 2007)

A Hybrid Approach for Tissue Recognition on Wound Images. - Héctor Mesa; Francisco J. Veredas 001; Laura Morente (HIS, 2008)

Imprecise correlated activity in self-organizing maps of spiking neurons. - Francisco J. Veredas 001; Héctor Mesa; Luis A. Martínez (Neural Networks, 2008)

Tissue Recognition Approach to Pressure Ulcer Area Estimation with Neural Networks. - Francisco J. Veredas 001; Héctor Mesa; Laura Morente (IWANN (1), 2009)

A hybrid learning approach to tissue recognition in wound images. - Francisco J. Veredas 001; Héctor Mesa; Laura Morente (Int. J. Intell. Comput. Cybern., 2009)

Predicting the Evolution of Pressure Ulcers. - Francisco J. Veredas 001; Héctor Mesa; Juan C. Morilla; Laura Morente (HEALTHINF, 2010)

Binary Tissue Classification on Wound Images With Neural Networks and Bayesian Classifiers. - Francisco J. Veredas 001; Héctor Mesa; Laura Morente (IEEE Trans. Medical Imaging, 2010)

PULAB - Computational-Intelligence Aided Management, Diagnosis, Teleassistance and e-Learning of Pressure Ulcers. - Laura Morente; Francisco J. Veredas 001; Héctor Mesa; Enrique Morris (HEALTHINF, 2011)

ePULab - An Adaptive e-Learning Tool for Pressure Ulcer Evaluation. - Laura Morente; Francisco J. Veredas 001 (HEALTHINF, 2013)

Computer-Aided Diagnosis in Wound Images with Neural Networks. - María Navas; Rafael M. Luque-Baena; Laura Morente; David Coronado; Rafael Rodríguez; Francisco J. Veredas 001 (IWANN (2), 2013)

A web-based e-learning application for wound diagnosis and treatment. - Francisco J. Veredas 001; Esperanza Ruiz-Bandera; Francisca Villa-Estrada; Juan F. Rufino-González; Laura Morente (Comput. Methods Programs Biomed., 2014)

Wound image evaluation with machine learning. - Francisco J. Veredas 001; Rafael M. Luque-Baena; Francisco J. Martín-Santos; Juan C. Morilla-Herrera; Laura Morente (Neurocomputing, 2015)

Efficient detection of wound-bed and peripheral skin with statistical colour models. - Francisco J. Veredas 001; Héctor Mesa; Laura Morente (Medical Biol. Eng. Comput., 2015)

Prediction of Protein Oxidation Sites. - Francisco J. Veredas 001; Francisco R. Cantón; Juan Carlos Aledo (IWANN (2), 2017)

L_1 L 1 -regularization Model Enriched with Biological Knowledge. - Daniel Urda; Francisco Aragón; Leonardo Franco; Francisco J. Veredas 001; José M. Jerez (IWBBIO (1), 2017)

A machine learning approach for predicting methionine oxidation sites. - Juan Carlos Aledo; Francisco R. Cantón; Francisco J. Veredas 001 (BMC Bioinform., 2017)

BLASSO: integration of biological knowledge into a regularized linear model. - Daniel Urda; Francisco Aragón; Rocío Bautista; Leonardo Franco; Francisco J. Veredas 001; Manuel Gonzalo Claros; José Manuel Jerez (BMC Syst. Biol., 2018)

MetODeep: A Deep Learning Approach for Prediction of Methionine Oxidation Sites in Proteins. - Guillermo López-García; José M. Jerez; Daniel Urda; Francisco J. Veredas 001 (IJCNN, 2019)

A Transfer-Learning Approach to Feature Extraction from Cancer Transcriptomes with Deep Autoencoders. - Guillermo López-García; José M. Jerez; Leonardo Franco; Francisco J. Veredas 001 (IWANN (1), 2019)

Addition of Pathway-Based Information to Improve Predictions in Transcriptomics. - Daniel Urda; Francisco J. Veredas 001; Ignacio Turias; Leonardo Franco (IWBBIO (2), 2019)

ICB-UMA at CLEF e-Health 2020 Task 1: Automatic ICD-10 coding in Spanish with BERT. - Guillermo López-García; José M. Jerez; Francisco J. Veredas 001 (CLEF (Working Notes), 2020)

ICB-UMA at CANTEMIST 2020: Automatic ICD-O Coding in Spanish with BERT. - Guillermo López-García; José M. Jerez; Francisco José Veredas 001 (IberLEF@SEPLN, 2020)

Combining feature engineering and feature selection to improve the prediction of methionine oxidation sites in proteins. - Francisco J. Veredas 001; Daniel Urda; José Luis Subirats; Francisco R. Cantón; Juan Carlos Aledo (Neural Comput. Appl., 2020)

Detection of Tumor Morphology Mentions in Clinical Reports in Spanish Using Transformers. - Guillermo López-García; José M. Jerez; Nuria Ribelles; Emilio Alba; Francisco J. Veredas 001 (IWANN (1), 2021)

Transformers for Clinical Coding in Spanish. - Guillermo López-García; José M. Jerez; Nuria Ribelles; Emilio Alba; Francisco J. Veredas 001 (IEEE Access, 2021)

Deep neural networks architecture driven by problem-specific information. - Daniel Urda; Francisco J. Veredas 001; Javier González-Enrique; Juan J. Ruiz-Aguilar; José M. Jerez; Ignacio J. Turias (Neural Comput. Appl., 2021)

Named Entity Recognition for De-identifying Real-World Health Records in Spanish. - Guillermo López-García; Francisco J. Moreno-Barea; Héctor Mesa; José M. Jerez; Nuria Ribelles; Emilio Alba; Francisco J. Veredas 001 (ICCS (3), 2023)

Explainable clinical coding with in-domain adapted transformers. - Guillermo López-García; José M. Jerez; Nuria Ribelles; Emilio Alba; Francisco J. Veredas 001 (J. Biomed. Informatics, 2023)

ClinLinker: Medical Entity Linking of Clinical Concept Mentions in Spanish. - Fernando Gallego Donoso; Guillermo López-García; Luis Gascó Sánchez; Martin Krallinger; Francisco J. Veredas 001 (ICCS (5), 2024)

Artificial Intelligence for Natural Language Processing of Clinical Text in Spanish for Real-World-Data Analysis (Text2RWD Project). - Francisco J. Veredas 001; Fernando Gallego Donoso; Guillermo López-García; Nuria Ribelles; Emilio Alba; José M. Jerez (SEPLN (Projects and Demonstrations), 2024)

Hybrid X-Linker: Automated Data Generation and Extreme Multi-label Ranking for Biomedical Entity Linking. - Pedro Ruas; Fernando Gallego Donoso; Francisco J. Veredas 001; Francisco M. Couto (CoRR, 2024)

Recognition and normalization of multilingual symptom entities using in-domain-adapted BERT models and classification layers. - Fernando Gallego Donoso; Francisco J. Veredas 001 (Database J. Biol. Databases Curation, 2024)

Named entity recognition for de-identifying Spanish electronic health records. - Francisco J. Moreno-Barea; Guillermo López-García; Héctor Mesa; Nuria Ribelles; Emilio Alba; José M. Jerez; Francisco J. Veredas 001 (Comput. Biol. Medicine, 2025)

Enhancing cross-encoders using knowledge graph hierarchy for medical entity linking in zero- and few-shot scenarios. - Fernando Gallego Donoso; Pedro Ruas; Francisco M. Couto; Francisco J. Veredas 001 (Knowl. Based Syst., 2025)