F. J. Veredas

发表

A computational tool to simulate correlated activity in neural circuits

J. M. Alonso, F. J. Veredas, F. J. Vico, 2004, Journal of Neuroscience Methods.

Self-organizing Maps of Spiking Neurons with Reduced Precision of Correlated Firing

Héctor Mesa, Francisco J. Veredas, Luis A. Martínez, 2007, ICANN.

Sulphur Atoms from Methionines Interacting with Aromatic Residues Are Less Prone to Oxidation

Francisco R. Cantón, F. J. Veredas, J. C. Aledo, 2015, Scientific Reports.

Methionine residues around phosphorylation sites are preferentially oxidized in vivo under stress conditions

Francisco R. Cantón, F. J. Veredas, J. C. Aledo, 2017, Scientific Reports.

Efficient detection of wound-bed and peripheral skin with statistical colour models

F. J. Veredas, Héctor Mesa, Laura Morente, 2015, Medical & Biological Engineering & Computing.

Factors determining the precision of the correlated firing generated by a monosynaptic connection in the cat visual pathway

Jose-Manuel Alonso, Francisco J Veredas, F. J. Veredas, 2005, The Journal of physiology.

monosynaptic connection in the cat visual pathway Factors determining the precision of the correlated firing generated by a

F. J. Veredas, J. Alonso, F. Vico, 2005 .

Héctor Mesa, Francisco J. Veredas, Luis A. Martínez, 2008, Neural Networks.

Transfer learning with convolutional neural networks for cancer survival prediction using gene-expression data

Guillermo López-García, José M Jerez, Leonardo Franco, 2020, PloS one.

A machine learning approach for predicting methionine oxidation sites

Francisco J. Veredas, Francisco R. Cantón, F. J. Veredas, 2017, BMC Bioinformatics.

A web-based e-learning application for wound diagnosis and treatment

Francisco J. Veredas, Laura Morente, F. J. Veredas, 2014, Comput. Methods Programs Biomed..

Prediction of Protein Oxidation Sites

Francisco J. Veredas, Francisco R. Cantón, F. J. Veredas, 2017, IWANN.

Animal-like adaptive behavior

Francisco J. Vico, Francisco J. Veredas, P. Mir, 2001, Artif. Intell. Eng..

Effectiveness of an e-learning tool for education on pressure ulcer evaluation.

F. J. Veredas, J. Morales‐Asencio, Laura Morente, 2014, Journal of clinical nursing.

Evolving networks of integrate-and-fire neurons

Francisco J. Vico, José M. Alonso, Francisco J. Veredas, 2006, Neurocomputing.

Wound image evaluation with machine learning

Rafael Marcos Luque Baena, Francisco J. Veredas, Laura Morente, 2015, Neurocomputing.

Binary Tissue Classification on Wound Images With Neural Networks and Bayesian Classifiers

Héctor Mesa, Francisco J. Veredas, Laura Morente, 2010, IEEE Transactions on Medical Imaging.

ePULab - An Adaptive e-Learning Tool for Pressure Ulcer Evaluation

Francisco J. Veredas, Laura Morente, F. J. Veredas, 2013, HEALTHINF.

Combining feature engineering and feature selection to improve the prediction of methionine oxidation sites in proteins

Daniel Urda, José Luis Subirats, Francisco J. Veredas, 2018, Neural Computing and Applications.

A machine learning approach for predicting methionine oxidation sites

F. J. Veredas, F. Cantón, J. Aledo, 2017, BMC Bioinformatics.

BLASSO: integration of biological knowledge into a regularized linear model

M. Gonzalo Claros, Daniel Urda, Leonardo Franco, 2018, BMC Systems Biology.

Explainable clinical coding with in-domain adapted transformers

F. J. Veredas, José M. Jerez, E. Alba, 2023, J. Biomed. Informatics.

Detection of Tumor Morphology Mentions in Clinical Reports in Spanish Using Transformers

Francisco J. Veredas, Nuria Ribelles, Emilio Alba, 2021, IWANN.

Transformers for Clinical Coding in Spanish

Francisco J. Veredas, Nuria Ribelles, Emilio Alba, 2021, IEEE Access.

ICB-UMA at CANTEMIST 2020: Automatic ICD-O Coding in Spanish with BERT

Guillermo López-García, F. J. Veredas, José María Jerez, 2020, IberLEF@SEPLN.

ICB-UMA at CLEF e-Health 2020 Task 1: Automatic ICD-10 coding in Spanish with BERT

F. J. Veredas, José M. Jerez, Guillermo López-García, 2020, Conference and Labs of the Evaluation Forum.

MetODeep: A Deep Learning Approach for Prediction of Methionine Oxidation Sites in Proteins

Daniel Urda, José M. Jerez, Francisco J. Veredas, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

A Transfer-Learning Approach to Feature Extraction from Cancer Transcriptomes with Deep Autoencoders

José M. Jerez, Francisco J. Veredas, Guillermo López-García, 2019, IWANN.

A hybrid learning approach to tissue recognition in wound images

Héctor Mesa, Francisco J. Veredas, Laura Morente, 2009, Int. J. Intell. Comput. Cybern..

PULAB - Computational-Intelligence Aided Management, Diagnosis, Teleassistance and e-Learning of Pressure Ulcers

Héctor Mesa, Francisco J. Veredas, Laura Morente, 2011, HEALTHINF.

Predicting the Evolution of Pressure Ulcers

Héctor Mesa, Francisco J. Veredas, Laura Morente, 2010, HEALTHINF.

Deep neural networks architecture driven by problem-specific information

Daniel Urda, Javier González-Enrique, Francisco J. Veredas, 2021, Neural Computing and Applications.