José M. Jerez
Orcid: 0000-0002-7858-2966Affiliations:
- University of Málaga, Spain
According to our database1,
José M. Jerez
authored at least 78 papers
between 2000 and 2025.
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Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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on orcid.org
On csauthors.net:
Bibliography
2025
Comput. Biol. Medicine, 2025
2024
Artificial Intelligence for Natural Language Processing of Clinical Text in Spanish for Real-World-Data Analysis (Text2RWD Project).
Proceedings of the Seminar of the Spanish Society for Natural Language Processing: Projects and System Demonstrations (SEPLN-CEDI-PD 2024) co-located with the 7th Spanish Conference on Informatics (CEDI 2024), 2024
Data Augmentation to Improve Molecular Subtype Prognosis Prediction in Breast Cancer.
Proceedings of the Computational Science - ICCS 2024, 2024
2023
J. Biomed. Informatics, March, 2023
Proceedings of the Bioinformatics and Biomedical Engineering, 2023
Proceedings of the Computational Science - ICCS 2023, 2023
2022
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022
Deep Learning Approach for the Prediction of the Concentration of Chlorophyll ɑ in Seawater. A Case Study in El Mar Menor (Spain).
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022
GAN-Based Data Augmentation for Prediction Improvement Using Gene Expression Data in Cancer.
Proceedings of the Computational Science - ICCS 2022, 2022
2021
Neural Comput. Appl., 2021
Detection of Tumor Morphology Mentions in Clinical Reports in Spanish Using Transformers.
Proceedings of the Advances in Computational Intelligence, 2021
2020
Improving learning and generalization capabilities of the C-Mantec constructive neural network algorithm.
Neural Comput. Appl., 2020
Expert Syst. Appl., 2020
Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020) co-located with 36th Conference of the Spanish Society for Natural Language Processing (SEPLN 2020), 2020
Proceedings of the Working Notes of CLEF 2020, 2020
2019
A Transfer-Learning Approach to Feature Extraction from Cancer Transcriptomes with Deep Autoencoders.
Proceedings of the Advances in Computational Intelligence, 2019
MetODeep: A Deep Learning Approach for Prediction of Methionine Oxidation Sites in Proteins.
Proceedings of the International Joint Conference on Neural Networks, 2019
2018
BMC Syst. Biol., 2018
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018
Data Dimension and Structure Effects in Predictive Performance of Deep Neural Networks.
Proceedings of the New Trends in Intelligent Software Methodologies, Tools and Techniques, 2018
2017
FPGA Implementation of Neurocomputational Models: Comparison Between Standard Back-Propagation and C-Mantec Constructive Algorithm.
Neural Process. Lett., 2017
Integr. Comput. Aided Eng., 2017
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017
Proceedings of the Bioinformatics and Biomedical Engineering, 2017
Proceedings of the Advances in Computational Intelligence, 2017
Solving Scheduling Problems with Genetic Algorithms Using a Priority Encoding Scheme.
Proceedings of the Advances in Computational Intelligence, 2017
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
2016
IEEE Trans. Parallel Distributed Syst., 2016
Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers.
IEEE Trans. Neural Networks Learn. Syst., 2016
Comput. Methods Programs Biomed., 2016
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2016
Deep Neural Network Architecture Implementation on FPGAs Using a Layer Multiplexing Scheme.
Proceedings of the Distributed Computing and Artificial Intelligence, 2016
2015
Soft Comput., 2015
Comput. Math. Methods Medicine, 2015
FPGA Implementation Comparison Between C-Mantec and Back-Propagation Neural Network Algorithms.
Proceedings of the Advances in Computational Intelligence, 2015
2014
IEEE Trans. Ind. Informatics, 2014
Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords.
J. Biomed. Informatics, 2014
Smart sensor/actuator node reprogramming in changing environments using a neural network model.
Eng. Appl. Artif. Intell., 2014
Proceedings of the IEEE Symposium on Intelligent Embedded Systems, 2014
Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2014
2013
Int. J. Medical Informatics, 2013
Analysis of Cancer Microarray Data using Constructive Neural Networks and Genetic Algorithms.
Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2013
A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel.
Proceedings of the Advances in Computational Intelligence, 2013
Proceedings of the Advances in Computational Intelligence, 2013
Implementation of the C-Mantec Neural Network Constructive Algorithm in an Arduino Uno Microcontroller.
Proceedings of the Advances in Computational Intelligence, 2013
Proceedings of the Advances in Computational Intelligence, 2013
2012
C-Mantec: A novel constructive neural network algorithm incorporating competition between neurons.
Neural Networks, 2012
Comput. Methods Programs Biomed., 2012
Proceedings of the Neural Information Processing - 19th International Conference, 2012
2011
Hybrid (Generalization-Correlation) Method for Feature Selection in High Dimensional DNA Microarray Prediction Problems.
Proceedings of the Advances in Computational Intelligence, 2011
2010
Multiclass Pattern Recognition Extension for the New C-Mantec Constructive Neural Network Algorithm.
Cogn. Comput., 2010
Missing data imputation using statistical and machine learning methods in a real breast cancer problem.
Artif. Intell. Medicine, 2010
Proceedings of the Advances in Neural Networks, 2010
Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles.
Proceedings of the Trends in Applied Intelligent Systems, 2010
2009
Proceedings of the Constructive Neural Networks, 2009
Constructive Neural Network Algorithms for Feedforward Architectures Suitable for Classification Tasks.
Proceedings of the Constructive Neural Networks, 2009
Neural Process. Lett., 2009
2008
A New Decomposition Algorithm for Threshold Synthesis and Generalization of Boolean Functions.
IEEE Trans. Circuits Syst. I Regul. Pap., 2008
Proceedings of the Artificial Neural Networks, 2008
2007
Neuronal selectivity, population sparseness, and ergodicity in the inferior temporal visual cortex.
Biol. Cybern., 2007
Early Breast Cancer Prognosis Prediction and Rule Extraction Using a New Constructive Neural Network Algorithm.
Proceedings of the Computational and Ambient Intelligence, 2007
MaxSet: An Algorithm for Finding a Good Approximation for the Largest Linearly Separable Set.
Proceedings of the Artificial Neural Networks, 2007
2006
A New Constructive Approach for Creating All Linearly Separable (Threshold) Functions.
Proceedings of the International Joint Conference on Neural Networks, 2006
Proceedings of the Artificial Neural Networks, 2006
Proceedings of the Artificial Neural Networks, 2006
2005
A Learning Rule to Model the Development of Orientation Selectivity in Visual Cortex.
Neural Process. Lett., 2005
Role of Function Complexity and Network Size in the Generalization Ability of Feedforward Networks.
Proceedings of the Computational Intelligence and Bioinspired Systems, 2005
Artificial neural networks and prognosis in medicine. Survival analysis in breast cancer patients.
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005
2004
Neural Comput. Appl., 2004
Appl. Intell., 2004
2003
Neural Process. Lett., 2003
A combined neural network and decision trees model for prognosis of breast cancer relapse.
Artif. Intell. Medicine, 2003
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003
A Learning Rule to Model the Development of Orientation Selectivity in Visual Cortex.
Proceedings of the Artificial Neural Nets Problem Solving Methods, 2003
Proceedings of the 11th European Symposium on Artificial Neural Networks, 2003
Proceedings of the Current Topics in Artificial Intelligence, 2003
2000
Un Modelo para la Prediccion de Recidiva de Pacientes Operados de Cancer de Mama (CMO) Basado en Redes Neuronales.
Inteligencia Artif., 2000