Research - Research groups - GE12 Learning and Artificial Neural Networks

GE12 Learning and Artificial Neural Networks

Our research group, Learning and Artificial Neural Networks (AYRNA) (TIC-148, "Junta de Andalucía"), was founded in 1994 by a small group of researchers interested in the field of Artificial Neural Networks. During the last years, the group has diversified its interest areas by searching solutions to different problems through machine learning and soft computing techniques (artificial neural networks, kernel methods, evolutionary algorithms, among others).

Currently, our group consists of 11 doctoral and 3 pre-doctoral researchers, and is led by Professor César Hervás Martínez as the main researcher of the group. Our group has published 328 works, including 148 international journal papers, and has been involved in 11 research projects, including one project with the European Space Agency. Finally, 28 PhD thesis have been supervised in AYRNA. Additional information can be found at AYRNA’s website. With respect to biomedicine, we propose to tackle problems such as donor-receptor matching in liver transplants, medical imaging analysis for melanoma detection and Parkinson disease detection including different severity degrees, and assignment of treatments for HIV/HCV patients.

The long-term objectives of the group are to contribute to the scientific community all the advances we achieve in the field of machine learning. As far as possible, we want to apply our techniques and algorithms to real societal problems, as we are already doing with dermatology, liver transplants, Parkinson's Disease, climate change and renewable energies, among others.

Among our achievements, we highlight the importance of the research carried out by our group in the field of liver transplantation, which has been awarded on many occasions by different entities both nationally and internationally.

We collaborate with different companies who may be interested in the application of our computational solutions. Among them are General Electric, Iberdrola, Astellas Pharma, among others.

Lines of Research

Ordinal classification: development of ordinal classification by evolutionary computation

Applications in donor-recipient matching in transplantation

New decision support system which leads to making the correct decision about receptor choice based on efficient and impartial criteria (principles of justice, efficiency and equity). A Rule-based system that aids medical experts in making decisions about the allocation of liver transplants.

Evolutionary neural networks

Deep learning

Multi-objective evolutionary algorithms

Automatic learning

New basis functions for neural networks

Time series

Applications in medical imaging diagnosis

Applications in renewable energies

Networks

DAMA network (TIN2015-70308-REDT)

MAPAS network (TIN2017-90567-REDT)

PAIDI TIC-148 - Learning and Artificial Neural Networks

Key Words

ordinal classification
artificial neural networks
processing of biomedical images
time series segmentation
regression models
ordinal regression
evolutionary computation

Información Adicional

Our website: AYRNA

Dr. Pedro Antonio Gutiérrez Peña

Principal Investigator

Projects

PROYECTOS EN 2024

Activos

Regional

D. Guijo-Rubio; TimeFlies: TIME series Forecasting and ordinaL classIfication applied to renewable Energies and atmospheric eventS; Funding Agency: Universidad de Córdoba & Junta de Andalucía; Reference: PP2F_L1_15. (01/10/2024 - 31/03/2026)

Nacional

P.A. Gutiérrez y C. Hervás-Martínez; Nuevos algoritmos para clasificación ordinal y modelos profundos: aplicaciones en clima, energías limpias y medio ambiente; Funding Agency: MICINN, conv. 2020 (Programa Estatal de I+D+i Orientada a los Retos de la Sociedad); Reference: PID2020-115454GB-C22. (01/09/2021 - 31/08/2024)

P.A. Gutiérrez y J.C. Fernández; Nuevos modelos EXplicables en clasificación Ordinal (NEXO): aplicaciones a energías renovables y biomedicina; Funding Agency: MCIU; Reference: PID2023-150663NB-C22. (01/09/2024 - 31/08/2027)

R.M. Gallardo, J. Olivares y A. Peña; Cátedra ENIA en Agricultura. Funding Agency: Secretaría de Estado de Digitalización e Inteligencia Artificial y Unión Europea (Next Generation); Reference: TSI-100921-2023-3. (01/01/2024 - 31/12/2027)

Internacional

R.M. Gallardo, J. Olivares y A. Peña; Test and Experiment Facilities for the Agri-Food Domain, AgriFoodTEF; Funding Agency: Comisión Europea; Reference: DIGITAL-2022-C-AI-02-101100622. (01/01/2024 - 31/12/2027)

PROYECTOS EN 2023

Activos

Nacional

PROYECTOS EN 2022

Activos

Regional

P.A. Gutiérrez; Métodos de Aprendizaje Profundo en clasificación Ordinal (MAP-ORDINAL). Funding Agency: Junta de Andalucía, PAIDI 2020; Reference: P20-00074. (05/10/2021 - 31/12/2022)

Nacional

PROYECTOS EN 2021

Activos

Regional

P.A. Gutiérrez; Métodos de Aprendizaje Profundo en clasificación Ordinal (MAP-ORDINAL). Funding Agency: Junta de Andalucía, PAIDI 2020; Reference: P20-00074. (05/10/2021 - 31/12/2022)

Nacional

Publications

Publications in 2025

Carbonero-Ruz M, Fernández-Navarro F, Durán-Rosal AM, Perez-Rodriguez J. A hybrid optimization and data-driven approach to understand the role of the risk-aversion profile parameter in portfolio optimization problems with shorting constraints. OPERATIONS RESEARCH PERSPECTIVES. 2025. -. DOI:10.1016/j.orp.2025.100353. IF: 3,7 Q2 D3

Gómez-Orellana AM, Rodríguez-Perálvarez ML, Guijo-Rubio D, Gutiérrez PA, Majumdar A, McCaughan GW, Taylor R, Tsochatzis EA, Hervás-Martínez C. Gender-Equity Model for Liver Allocation Using Artificial Intelligence (GEMA-AI) for Waiting List Liver Transplant Prioritization. CLINICAL GASTROENTEROLOGY AND HEPATOLOGY. 2025. 2187-2196. DOI:10.1016/j.cgh.2024.12.010. IF: 12,2 Q1 D1

Calleja R, Rivera M, Guijo-Rubio D, Hessheimer AJ, de la Rosa G, Gastaca M, Otero A, Ramírez P, Boscà-Robledo A, Santoyo J, Gómez LMM, del Moral JV, Fundora Y, Lladó L, Loinaz C, Jiménez-Garrido MC, Rodríguez-Laíz G, López-Baena JA, Charco R, Varo E, Rotellar F, Alonso A, Rodríguez-Sanjuan JC, Blanco G, Nuño J, Pacheco D, Coll E, Domínguez-Gil B, Fondevila C, Ayllón MD, Durán M, Ciria R, Gutiérrez PA, Gómez-Orellana A, Hervás-Martínez C, Briceño J. Machine Learning Algorithms in Controlled Donation After Circulatory Death Under Normothermic Regional Perfusion: A Graft Survival Prediction Model. TRANSPLANTATION. 2025. e362-e370. DOI:10.1097/tp.0000000000005312; 10.1097/TP.0000000000005312. IF: 5 Q1 D1

Salcedo-Sanz S, Guijo-Rubio D, Perez-Aracil J, Peláez-Rodriguez C, Gomez-Orellana AM, Gutierrez-Peña PA. Artificial Intelligence-Based Methods and Algorithms in Fog and Atmospheric Low-Visibility Forecasting. ATMOSPHERE. 2025. -. DOI:10.3390/atmos16091073. IF: 2,3 Q3 D

Barbero-Gómez J, Cruz RPM, Cardoso JS, Gutiérrez PA, Hervás-Martínez C. CNN explanation methods for ordinal regression tasks. NEUROCOMPUTING. 2025. -. DOI:10.1016/j.neucom.2024.128878. IF: 6,5 Q1 D2

Ayllón-Gavilán R, Guijo-Rubio D, Gutiérrez PA, Bagnall A, Hervás-Martínez C. Convolutional-and Deep Learning-Based Techniques for Time Series Ordinal Classification. IEEE TRANSACTIONS ON CYBERNETICS. 2025. 537-549. DOI:10.1109/TCYB.2024.3498100. IF: 10,5 Q1 D1

Bérchez-Moreno F, Ayllón-Gavilán R, Vargas VM, Guijo-Rubio D, Hervás-Martínez C, Fernández JC, Gutiérrez PA. dlordinal: A Python package for deep ordinal classification. NEUROCOMPUTING. 2025. -. DOI:10.1016/j.neucom.2024.129305. IF: 6,5 Q1 D2

Gómez-Orellana AM, Vega-Bayo M, Guijo-Rubio D, Pérez-Aracil J, Vargas VM, Gutiérrez PA, Prieto-Godino L, Salcedo-Sanz S, Hervás-Martínez C. Enhancing wind speed prediction in wind farms through ordinal classification. ENERGY AND AI. 2025. -. DOI:10.1016/j.egyai.2025.100596. IF: 9,6 Q1 D1

Durán-Rosal AM, Ashley T, Pérez-Rodríguez J, Fernández-Navarro F. Global and Diverse Ensemble model for regression. NEUROCOMPUTING. 2025. -. DOI:10.1016/j.neucom.2025.130520. IF: 6,5 Q1 D2

Pérez-Aracil J, Peláez-Rodriguez C, McAdam R, Squintu A, Marina CM, Lorente-Ramos E, Luther N, Torralba V, Scoccimarro E, Cavicchia L, Giuliani M, Zorita E, Hansen F, Barriopedro D, García-Herrera R, Gutiérrez PA, Luterbacher J, Xoplaki E, Castelletti A, Salcedo-Sanz S. Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection. WEATHER AND CLIMATE EXTREMES. 2025. -. DOI:10.1016/j.wace.2025.100792. IF: 6,9 Q1 D1

Rosati R, Romeo L, Vargas VM, Gutiérrez PA, Frontoni E, Hervás-Martínez C. Learning Ordinal-Hierarchical Constraints for Deep Learning Classifiers. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. 2025. 4765-4778. DOI:10.1109/TNNLS.2024.3360641. IF: 8,9 Q1 D1

Ayllón-Gavilán R, Gómez-Orellana AM, Vargas VM, Guijo-Rubio D, Pérez-Aracil J, Salcedo-Sanz S, Gutiérrez PA, Hervá-Martínez C. Simultaneous multi-step wind speed prediction on multiple farms using multi-task deep learning. INTEGRATED COMPUTER-AIDED ENGINEERING. 2025. 366-378. DOI:10.1177/10692509251337224. IF: 5,3 Q1 D2

de los Ríos-Berjillos A, Rodero-Cosano ML, Ruiz-Lozano M, Mesa-Pérez E. The Institutionalization of an Ethical Culture Through the Implementation of Compliance Systems. CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT. 2025. 6416-6433. DOI:10.1002/csr.70017. IF: 9,1 Q1 D1

Publications in 2024

F. Bérchez-Moreno, R. Ayllón-Gavilán, V.M. Vargas, D. Guijo-Rubio, C. Hervás-Martínez, J.C. Fernández y P.A. Gutiérrez. dlordinal: A Python package for deep ordinal classification. NEUROCOMPUTING 2025. DOI: 10.1016/j.neucom.2024.129305. IF: 6.5 Q1

R. Rosati, L. Romeo, V.M. Vargas, P.A. Gutiérrez, E. Frontoni y C. Hervás-Martínez. Learning Ordinal–Hierarchical Constraints for Deep Learning Classifiers. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2025. DOI: 10.1109/TNNLS.2024.3360641. IF: 8.9 Q1 D1

J. Barbero-Gómez, R.P. Cruz, J.S. Cardoso, P.A. Gutiérrez y C. Hervás-Martínez. CNN Explanation Methods for Ordinal Regression Tasks. NEUROCOMPUTING 2025. DOI: 10.1016/j.neucom.2024.128878. IF: 6.5 Q1

R. Calleja-Lozano, M. Rivera-Gavilán, D. Guijo-Rubio, A.J. Hessheimer, G. D. la Rosa, M. Gastaca, A. Otero, P. Ramirez, A. Boscà-Robledo, J. Santoyo-Santoyo, L.M. Marín-Gómez, J. Del Villar Moral, Y. Fundora, L. Lladó, C. Loinaz, M.C. Jiménez-Garrido, G. Rodríguez-Laíz, J.A. López-Baena, R. Charco, E. Varo, F. Rotellar, A. Alonso, J.C. Rodríguez-Sanjuan, G. Blanco, J. Nuño, D. Pacheco, E. Coll, B. Domínguez-Gil, C. Fontdevila, M.D. Ayllón, M. Durán, R. Ciria, P.A. Gutiérrez, A.M. Gómez-Orellana, C. Hervás-Martínez y J. Briceño. Machine learning algorithms in controlled donation after circulatory death under normothermic regional perfusion: A graft survival prediction model. TRANSPLANTATION 2025. DOI:10.1097/TP.0000000000005312. IF: 5.0 Q1 D1

A.M. Gómez-Orellana, M. Rodríguez-Perálvarez, D. Guijo-Rubio, P.A. Gutiérrez, A. Majumdar, G.W. McCaughan, R. Taylor, E. Tsochatzis y C. Hervás-Martínez. Gender-Equity Model for Liver Allocation using Artificial Intelligence (GEMA-AI) for waiting list liver transplant prioritization. CLINICAL GASTROENTEROLOGY AND HEPATOLOGY 2025. DOI: 10.1016/j.cgh.2024.12.010. IF: 11.6 Q1 D1

J. Barbero-Gómez, P.A. Gutiérrez y C. Hervás-Martínez. Error-Correcting Output Codes in the Framework of Deep Ordinal Classification. NEURAL PROCESSING LETTERS 2025. DOI: 10.1007/s11063-022-10824-7. IF: 2.6 Q3

Publications in 2024

Bérchez-Moreno F, Durán-Rosal AM, Martínez CH, Gutiérrez PA, Fernández JC. A memetic dynamic coral reef optimisation algorithm for simultaneous training, design, and optimisation of artificial neural networks. SCIENTIFIC REPORTS. 2024. DOI: 10.1038/s41598-024-57654-2. IF: 3,8 Q1 D2

Morales-Martín A, Mesas-Carrascosa FJ, Gutiérrez PA, Pérez-Porras FJ, Vargas VM, Hervás-Martínez C. Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds. SENSORS. 2024. DOI: 10.3390/s24072168. IF: 3,4 Q2 D4

Vargas VM, Gómez-Orellana AM, Gutiérrez PA, Hervás-Martínez C, Guijo-Rubio D. EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height. KNOWLEDGE-BASED SYSTEMS. 2024. DOI: 10.1016/j.knosys.2024.112223. IF: 7,2 Q1 D2

Trinidad-Gutiérrez I, Vázquez-Borrego MC, Aguilera-Fernández E, Velez-Castaño JE, Muriel-López CE, Rodríguez-Ortíz L, Gómez A, Berchez-Moreno F, Hervás C, Romero-Ruiz A, Arjona-Sánchez A. Efficacy of systemic Chemotherapy on high-risk stage II and III Mucnious colon cancer. CHEMUCCA study part I. EJSO. 2024. DOI: 10.1016/j.ejso.2024.108642. IF: 3,5 Q1 D2

Bérchez-Moreno F, Fernández JC, Hervás-Martínez C, Gutiérrez PA. Fusion of standard and ordinal dropout techniques to regularise deep models. INFORMATION FUSION. 2024. DOI: 10.1016/j.inffus.2024.102299. IF: 14,7 Q1 D1

Peláez-Rodríguez C, Pérez-Aracil J, Gómez-Orellana AM, Guijo-Rubio D, Vargas VM, Gutiérrez PA, Hervás-Martínez C, Salcedo-Sanz S. Fuzzy-based ensemble methodology for accurate long-term prediction and interpretation of extreme significant wave height events. APPLIED OCEAN RESEARCH. 2024. DOI: 10.1016/j.apor.2024.104273. IF: 4,3 Q1 D1

Rodríguez-Perálvarez ML, de la Rosa G, Gómez-Orellana AM, Aguilera MV, Vicente TP, Pereira S, Ortiz ML, Pagano G, Suarez F, Grande RG, Cachero A, Tomé S, Barreales M, Mateos RM, Pascual S, Romero M, Bilbao I, Martín CA, Otón E, Diéguez LG, Espinosa MD, Milla AA, Fernández GB, Lorente S, Lavín AC, García AR, Cano CS, Cepeda-Franco C, Pons JA, Colmenero J, Guijo-Rubio D, Otero A, Navarrete AA, Moreno SR, Soler MR, Martínez CH, Gastaca M. GEMA-Na and MELD 3.0 severity scores to address sex disparities for accessing liver transplantation: a nationwide retrospective cohort study. ECLINICALMEDICINE. 2024. DOI: 10.1016/j.eclinm.2024.102737. IF: 9,6 Q1 D1

Gómez-Orellana AM, Guijo-Rubio D, Gutiérrez PA, Hervás-Martínez C, Vargas VM. ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE. 2024. DOI: 10.1016/j.engappai.2024.108462. IF: 7,5 Q1 D1

M. Rodríguez-Perálvez, G. de la Rosa, A.M. Gómez-Orellana, V.A. Sancho, T. Pascual-Vicente, S. Pereira, M.L. Ortiz, G. Pagano, F. Suárez, R. González-Grande, A. Cachero, S. Tomé, M.B. Valbuena, R. Martin-Mateos, S. Pascual, M.R. Cristóbal, I. Bilbao, C.A. Martin, E. Oton, M.L. Dieguez, M.D. Aguilar, A. Arias, G. Blanco, S.L. Perez, A. Cuadrado, A.R. García, C.S. Cano, C.C. Franco, J.A. Pons, J. Colmenero, D. Guijo-Rubio, A.O. Ferreiro, N.H. Aretxabaleta, S.R. Moreno, M.R. Soler, C. Hervás-Martínez y M. Gastaca. GEMA-Na and MELD 3.0 severity scores to address sex disparities for accessing liver transplantation: a nationwide retrospective cohort study. ECLINICALMEDICINE 2024. DOI: 10.1016/j.eclinm.2024.102737. IF: 10.0 Q1 D1

V.M. Vargas, A.M. Gómez-Orellana, P.A. Gutiérrez, C. Hervás-Martínez y D. Guijo-Rubio. EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height. KNOWLEDFE-BASED SYSTEMS 2024. DOI: 10.1016/j.knosys.2024.112223 IF: 7.2 Q1

M. Middlehurst, A. Ismail-Fawaz, A. Guillaume, C. Holder, D. Guijo-Rubio, G. Bulatova, L. Tsaprounis, L. Mentel, M. Walter, P. Schäfer y A. Bagnall. aeon: a Python toolkit for learning from time series. JOURNAL OF MACHINE LEARNING RESEARCH 2024. DOI: https://jmlr.org/papers/v25/23-1444.html. IF: 5.2 Q1

A.M. Gómez-Orellana, D. Guijo-Rubio, P.A. Gutiérrez, C. Hervás-Martínez y V.M. Vargas. ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target. ENGENIEERING APLLICATIONS OF ARTIFICIAL INTELLIGENCE 2024. DOI: 10.1016/j.engappai.2024.108462. IF: 8.0 Q1 D1

. Trinidad-Gutiérrez, M.C. Vázquez-Borrego, E. Aguilera-Fernández, J.E. Velez-Castaño, C.E. Muriel-López, L. Rodríguez-Ortíz, A.M. Gómez-Orellana, F. Bérchez-Moreno, C. Hervás-Martínez, A. Romero-Ruiz y Á. Arjona-Sánchez. Efficacy of systemic Chemotherapy on high-risk stage II and III Mucnious colon cancer. CHEMUCCA study part I. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2024. DOI: 10.1016/j.ejso.2024.108642. IF: 2.9 Q1

F. Bérchez-Moreno, J.C. Fernández, C. Hervás-Martínez y P.A. Gutiérrez. Fusion of standard and ordinal dropout techniques to regularise deep models. INFORMATION FUSION 2024. DOI: 10.1016/j.inffus.2024.102299. IF: 15.5 Q1 D1

D. Guijo-Rubio, M. Middlehurst, G. Arcencio, D.F. Silva y A. Bagnall. Unsupervised feature based algorithms for time series extrinsic regression. DATA MINING AND KNOWLEDGE DISCOVERY 2024. DOI: 10.1007/s10618-024-01027-w. IF: 4.3 Q2

Publications in 2023

C. Perales-González, J. Pérez-Rodríguez y A.M. Durán-Rosal. Boosting ridge for the extreme learning machine globally optimised for classification and regression problems. SCIENTIFIC REPORTS 2023. DOI: 10.1038/s41598-023-38948-3. IF: 3.8 Q1

A.M. Durán Rosal, A. Durán-Fernández, F. Fernández-Navarro y M. Carbonero-Ruz. A multi-class classification model with parametrized target outputs for randomized-based feedforward neural networks. APPLIED SOFT COMPUTING 2023. DOI: 10.1016/j.asoc.2022.109914. IF: 7.2 Q1

C. Perales-González, J. Pérez-Rodríguez y A.M. Durán-Rosal. Boosting ridge for the extreme learning machine globally optimised for classification and regression problems. SCIENTIFIC REPORTS 2023. DOI: 10.1038/s41598-023-38948-3. IF: 3.8 Q1

Publications in 2024

F. Bérchez-Moreno, A.M. Durán-Rosal, C. Hervás-Martínez, P.A. Gutiérrez y J.C. Fernández. A memetic dynamic coral reef optimisation algorithm for simultaneous training, design, and optimisation of artificial neural networks. SCIENTIFIC REPORTS 2024. DOI: 10.1038/s41598-024-57654-2. IF: 3.9 Q1

M. Rodríguez-Perálvez, G. de la Rosa, A.M. Gómez-Orellana, V.A. Sancho, T. Pascual-Vicente, S. Pereira, M.L. Ortiz, G. Pagano, F. Suárez, R. González-Grande, A. Cachero, S. Tomé, M.B. Valbuena, R. Martin-Mateos, S. Pascual, M.R. Cristóbal, I. Bilbao, C.A. Martin, E. Oton, M.L. Dieguez, M.D. Aguilar, A. Arias, G. Blanco, S.L. Perez, A. Cuadrado, A.R. García, C.S. Cano, C.C. Franco, J.A. Pons, J. Colmenero, D. Guijo-Rubio, A.O. Ferreiro, N.H. Aretxabaleta, S.R. Moreno, M.R. Soler, C. Hervás-Martínez y M. Gastaca. GEMA-Na and MELD 3.0 severity scores to address sex disparities for accessing liver transplantation: a nationwide retrospective cohort study. ECLINICALMEDICINE 2024. DOI: 10.1016/j.eclinm.2024.102737. IF: 10.0 Q1 D1

V.M. Vargas, A.M. Gómez-Orellana, P.A. Gutiérrez, C. Hervás-Martínez y D. Guijo-Rubio. EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height. KNOWLEDFE-BASED SYSTEMS 2024. DOI: 10.1016/j.knosys.2024.112223 IF: 7.2 Q1

M. Middlehurst, A. Ismail-Fawaz, A. Guillaume, C. Holder, D. Guijo-Rubio, G. Bulatova, L. Tsaprounis, L. Mentel, M. Walter, P. Schäfer y A. Bagnall. aeon: a Python toolkit for learning from time series. JOURNAL OF MACHINE LEARNING RESEARCH 2024. DOI: https://jmlr.org/papers/v25/23-1444.html. IF: 5.2 Q1

A.M. Gómez-Orellana, D. Guijo-Rubio, P.A. Gutiérrez, C. Hervás-Martínez y V.M. Vargas. ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target.
ENGENIEERING APLLICATIONS OF ARTIFICIAL INTELLIGENCE 2024. DOI: 10.1016/j.engappai.2024.108462. IF: 8.0 Q1 D1
I. Trinidad-Gutiérrez, M.C. Vázquez-Borrego, E. Aguilera-Fernández, J.E. Velez-Castaño, C.E. Muriel-López, L. Rodríguez-Ortíz, A.M. Gómez-Orellana, F. Bérchez-Moreno, C. Hervás-Martínez, A. Romero-Ruiz y Á. Arjona-Sánchez. Efficacy of systemic Chemotherapy on high-risk stage II and III Mucnious colon cancer. CHEMUCCA study part I. EUROPEAN JOURNAL OF SURGICAL ONCOLOGY 2024. DOI: 10.1016/j.ejso.2024.108642. IF: 2.9 Q1

F. Bérchez-Moreno, J.C. Fernández, C. Hervás-Martínez y P.A. Gutiérrez. Fusion of standard and ordinal dropout techniques to regularise deep models. INFORMATION FUSION 2024. DOI: 10.1016/j.inffus.2024.102299. IF: 15.5 Q1 D1

D. Guijo-Rubio, M. Middlehurst, G. Arcencio, D.F. Silva y A. Bagnall. Unsupervised feature based algorithms for time series extrinsic regression. DATA MINING AND KNOWLEDGE DISCOVERY 2024. DOI: 10.1007/s10618-024-01027-w. IF: 4.3 Q2

Publications in 2025

R. Ayllón-Gavilán, D. Guijo-Rubio, P.A. Gutiérrez, A. Bagnall y C. Hervás-Martínez. Convolutional and Deep Learning based techniques for Time Series Ordinal Classification. IEEE TRANSACTIONS ON CYBERNETICS 2025. DOI: 10.1109/TCYB.2024.3498100. IF: 10.5 Q1 D1

F. Bérchez-Moreno, R. Ayllón-Gavilán, V.M. Vargas, D. Guijo-Rubio, C. Hervás-Martínez, J.C. Fernández y P.A. Gutiérrez. dlordinal: A Python package for deep ordinal classification. NEUROCOMPUTING 2025. DOI: 10.1016/j.neucom.2024.129305. IF: 6.5 Q1

R. Rosati, L. Romeo, V.M. Vargas, P.A. Gutiérrez, E. Frontoni y C. Hervás-Martínez. Learning Ordinal–Hierarchical Constraints for Deep Learning Classifiers. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2025. DOI: 10.1109/TNNLS.2024.3360641. IF: 8.9 Q1 D1

J. Barbero-Gómez, R.P. Cruz, J.S. Cardoso, P.A. Gutiérrez y C. Hervás-Martínez. CNN Explanation Methods for Ordinal Regression Tasks. NEUROCOMPUTING 2025. DOI: 10.1016/j.neucom.2024.128878. IF: 6.5 Q1

R. Calleja-Lozano, M. Rivera-Gavilán, D. Guijo-Rubio, A.J. Hessheimer, G. D. la Rosa, M. Gastaca, A. Otero, P. Ramirez, A. Boscà-Robledo, J. Santoyo-Santoyo, L.M. Marín-Gómez, J. Del Villar Moral, Y. Fundora, L. Lladó, C. Loinaz, M.C. Jiménez-Garrido, G. Rodríguez-Laíz, J.A. López-Baena, R. Charco, E. Varo, F. Rotellar, A. Alonso, J.C. Rodríguez-Sanjuan, G. Blanco, J. Nuño, D. Pacheco, E. Coll, B. Domínguez-Gil, C. Fontdevila, M.D. Ayllón, M. Durán, R. Ciria, P.A. Gutiérrez, A.M. Gómez-Orellana, C. Hervás-Martínez y J. Briceño. Machine learning algorithms in controlled donation after circulatory death under normothermic regional perfusion: A graft survival prediction model. TRANSPLANTATION 2025. DOI: 10.1097/TP.0000000000005312. IF: 5.0 Q1 D1

A.M. Gómez-Orellana, M. Rodríguez-Perálvarez, D. Guijo-Rubio, P.A. Gutiérrez, A. Majumdar, G.W. McCaughan, R. Taylor, E. Tsochatzis y C. Hervás-Martínez. Gender-Equity Model for Liver Allocation using Artificial Intelligence (GEMA-AI) for waiting list liver transplant prioritization. CLINICAL GASTROENTEROLOGY AND HEPATOLOGY 2025. DOI: 10.1016/j.cgh.2024.12.010. IF: 11.6 Q1 D1

J. Barbero-Gómez, P.A. Gutiérrez y C. Hervás-Martínez. Error-Correcting Output Codes in the Framework of Deep Ordinal Classification. NEURAL PROCESSING LETTERS 2025. DOI: 10.1007/s11063-022-10824-7. IF: 2.6 Q3

Publications in 2026

R. Ayllón-Gavilán, F.J. Martínez-Estudillo, D. Guijo-Rubio, C. Hervás-Martínez y P.A. Gutiérrez. Splitting criteria for ordinal decision trees: An experimental study. PATTERN RECOGNITION 2026. DOI: 10.1016/j.patcog.2025.112273. IF: 7.6 Q1 D1

Members

Principal Investigator
Pedro Antonio Gutiérrez Peña

Researchers
Antonio M Durán Rosal
Juan Carlos Fernández Caballero
David Guijo Rubio
Javier Sánchez Monedero

Post-Doctoral Researchers
Antonio Gómez Orellana
Víctor Vargas Yun

Pre-Doctoral Researchers
Rafael Ayllón Gavilán
Francisco Bérchez Moreno
Francisco Moreno Cano
Marcos Rivera Gavilán

Nursing, Technical, and Administrative Staff
Miguel Ángel Contreras Córdoba
Ángel Sevilla Molina

Collaborators
César Hervás Martínez