Year: 2024 (23)

• 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 and 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, Vol. 50, November, 2024. JCR (2023): 3.5, Position: 31/290 (Q1), Category: SURGERY. [More] [Bibtex] [RIS] [MODS]
• J. Pérez-Aracil, D. Fister, C.M. Marina, C. Peláez-Rodríguez, L. Cornejo-Bueno, P.A. Gutiérrez, M. Giuliani, A. Castelleti and S. Salcedo-Sanz. "Long-term temperature prediction with hybrid autoencoder algorithms", Applied Computing and Geosciences, Vol. 23, September, 2024, pp. 100185. JCR (2023): 2.6, Position: 98/253 (Q2), Category: GEOSCIENCES, MULTIDISCIPLINARY. [More] [Bibtex] [RIS] [MODS]
• A.M. Gómez-Orellana, D. Guijo-Rubio, P.A. Gutiérrez, C. Hervás-Martínez and V.M. Vargas. "ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target", Engineering Applications of Artificial Intelligence, Vol. 133(E), July, 2024, pp. 1-18. JCR (2023): 7.5, Position: 12/180 (Q1D1), Category: ENGINEERING, MULTIDISCIPLINARY.. [More] [Bibtex] [RIS] [MODS]
• A. Bagnall, M. Middlehurst, G. Forestier, A. Ismail-Fawaz, A. Guillaume, D. Guijo-Rubio, C.W. Tan, A. Dempster and G.I. Webb. "A Hands-on Introduction to Time Series Classification and Regression". Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2024. pp. 6410-6411. [More] [Bibtex] [RIS] [MODS]
• M. Middlehurst, A. Ismail-Fawaz, A. Guillaume, C. Holder, D. Guijo-Rubio, G. Bulatova, L. Tsaprounis, L. Mentel, M. Walter, P. Schäfer and Others. "aeon: a Python toolkit for learning from time series", Journal of Machine Learning Research. 2024. [More] [Bibtex] [RIS] [MODS]
• V.M. Vargas, A.M. Gómez-Orellana, P.A. Gutiérrez, C. Hervás-Martínez and D. Guijo-Rubio. "EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height", Knowledge-Based Systems, Vol. 300. 2024, pp. 1-14. JCR (2023): 7.2, Position: 27/197 (Q1), Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. [More] [Bibtex] [RIS] [MODS]
• A. Morales-Martín, F.-J. Mesas-Carrascosa, P.A. Gutiérrez, F.-J. Pérez-Porras, V.M. Vargas and C. Hervás-Martínez. "Deep Ordinal Classification in Forest Areas Using Light Detection and Ranging Point Clouds", Sensors, Vol. 24(7). 2024, pp. 1-18. JCR(2023): 3.4, Position: 24/76 (Q2) Category: INSTRUMENTS & INSTRUMENTATION. [More] [Bibtex] [RIS] [MODS]
• M.L. Perálvarez et al.. "UTILIDAD DEL GENDER-EQUITY MODEL FOR LIVER ALLOCATION (GEMA) EN UN CONTEXTO DE ACORTAMIENTO DE LA LISTA DE ESPERA DE TRASPLANTE HEPÁTICO". 48.º Congreso Anual de la Asociación Española para el Estudio del Hígado. 2024. [More] [Bibtex] [RIS] [MODS]
• M. Rodríguez-Perálvez et al.. "GEMA-Na and MELD 3.0 severity scores to address sex disparities for accessing liver transplantation: a nationwide retrospective cohort study". eClinalMedicine. Agosto. 2024. pp. 102737. [More] [Bibtex] [RIS] [MODS]
• C.M. Marina, E. Lorente-Ramos, R. Ayllón-Gavilán, P.A. Gutiérrez, J. Pérez-Aracil and S. Salcedo-Sanz. "Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction". Advances in Artificial Intelligence. Junio. 2024. pp. 223–232. [More] [Bibtex] [RIS] [MODS]
• M. Rodríguez-Perálvez et al.. "TOP-002 Validation of the gender-equity model for liver allocation (GEMA) in a nationwide cohort of liver transplant candidates in Spain". Journal of Hepatology. Junio. 2024. pp. S365-S366. [More] [Bibtex] [RIS] [MODS]
• M. Rodríguez-Perálvez, A.M. Gómez-Orellana, D. Guijo-Rubio, P.A. Gutiérrez, A. Majumdar, G. McCaughan, R. Taylor, C. Hervás-Martínez and E. Tsochatzis. "OS-024 The gender-equity model for liver allocation built on artificial intelligence (GEMA-AI) improves outcome predictions among liver transplant candidates". Journal of Hepatology. Junio. 2024. [More] [Bibtex] [RIS] [MODS]
• A.M. Gómez-Orellana, V.M. Vargas, P.A. Gutiérrez, J. Pérez-Aracil, S. Salcedo-Sanz, C. Hervás-Martínez and D. Guijo-Rubio. "Energy Flux Prediction Using an Ordinal Soft Labelling Strategy". Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. Mayo. 2024. pp. 283–292. [More] [Bibtex] [RIS] [MODS]
• A.M. Gómez-Orellana, V.M. Vargas, D. Guijo-Rubio, J. Pérez-Aracil, P.A. Gutiérrez, S. Salcedo-Sanz and C. Hervás-Martínez. "Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm". Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. Mayo. 2024. pp. 293–302. [More] [Bibtex] [RIS] [MODS]
• M. Vega-Bayo, A.M. Gómez-Orellana, V.M. Vargas, D. Guijo-Rubio, L. Cornejo-Bueno, J. Pérez-Aracil and S. Salcedo-Sanz. "Data Augmentation Techniques for Extreme Wind Prediction Improvement". Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. Mayo. 2024. pp. 303–313. [More] [Bibtex] [RIS] [MODS]
• R. Ayllón-Gavilán, D. Guijo-Rubio, P.A. Gutiérrez and C. Hervás-Martínez. "O-Hydra: A Hybrid Convolutional and Dictionary-Based Approach to Time Series Ordinal Classification". Advances in Artificial Intelligence. Junio. 2024. CAEPIA. [More] [Bibtex] [RIS] [MODS]
• V.M. Vargas, A.M. Gómez-Orellana, D. Guijo-Rubio, F. Bérchez-Moreno, P.A. Gutiérrez and C. Hervás-Martínez. "Age Estimation Using Soft Labelling Ordinal Classification Approaches". Advances in Artificial Intelligence. Junio. 2024. CAEPIA. pp. 40-49. [More] [Bibtex] [RIS] [MODS]
• D. Guijo-Rubio, M. Middlehurst, G. Arcencio, D.F. Silva and A. Bagnall. "Unsupervised feature based algorithms for time series extrinsic regression", Data Mining and Knowledge Discovery, Mayo, 2024, pp. 1-45. JCR (2023): 2.8, Position: 98/197 (Q2), Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. [More] [Bibtex] [RIS] [MODS]
• F. Bérchez-Moreno, A.M. Durán-Rosal, C. Hervás-Martínez, P.A. Gutiérrez and J.C. Fernández. "A memetic dynamic coral reef optimisation algorithm for simultaneous training, design, and optimisation of artificial neural networks", Scientific Reports, Vol. 14, Marzo, 2024, pp. 6961. JCR (2023): 3.8, Position: 25/134 (Q1), Category: MULTIDISCIPLINARY SCIENCES. [More] [Bibtex] [RIS] [MODS]
• C. Peláez-Rodríguez, J. Pérez-Aracil, C.M. Marina, L. Prieto-Godino, C. Casanova-Mateo, P.A. Gutiérrez and S. Salcedo-Sanz. "A general explicable forecasting framework for weather events based on ordinal classification and inductive rules combined with fuzzy logic", Knowledge-Based Systems, Vol. 291, Mayo, 2024, pp. 111556. JCR(2023): 7.2 Position: 27/197 (Q1) Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. [More] [Bibtex] [RIS] [MODS]
• F. Bérchez-Moreno, J.C. Fernández, C. Hervás-Martínez and P.A. Gutiérrez. "Fusion of standard and ordinal dropout techniques to regularise deep models", Information Fusion, Vol. 106, Febrero, 2024. JCR 2023: 14.7, Position: 2/143 (Q1), Category: COMPUTER SCIENCE, THEORY & METHODS. [More] [Bibtex] [RIS] [MODS]
• A. Guersenzvaig and J. Sánchez-Monedero. "AI research assistants, intrinsic values, and the science we want", AI & SOCIETY, Febrero, 2024. JCR 2023: 2.9, Position: 95/197 (Q2), Category: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE. [More] [Bibtex] [RIS] [MODS]
• R. Rosati, L. Romeo, V.M. Vargas, P.A. Gutiérrez, E. Frontoni and C. Hervás-Martínez. "Learning Ordinal–Hierarchical Constraints for Deep Learning Classifiers", IEEE Transactions on Neural Networks and Learning Systems, Febrero, 2024, pp. 1-14. JCR(2023): 10.2, Position: 7/143 (Q1) Category: COMPUTER SCIENCE, THEORY & METHODS. [More] [Bibtex] [RIS] [MODS]

Year: 2023 (2)

• C. Perales-González, J. Pérez-Rodríguez and A.M. Durán-Rosal. "Boosting ridge for the extreme learning machine globally optimised for classification and regression problems", Scientific Reports, Vol. 13, July, 2023, pp. 11809. JCR(2023): 3.8 Position: 25/134 (Q1) Category: MULTIDISCIPLINARY SCIENCES. [More] [Bibtex] [RIS] [MODS]
• V.M. Vargas, P.A. Gutiérrez, R. Rosati, L. Romeo, E. Frontoni and C. Hervás-Martínez. "Exponential loss regularisation for encouraging ordinal constraint to shotgun stocks quality assessment", Applied Soft Computing, Vol. 138(110191), May, 2023. JCR(2023): 7.2, Position: 15/169 (Q1) Category: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS. [More] [Bibtex] [RIS] [MODS]