Fighting the disagreement in Explainable Machine Learning with consensus. - Antonio-Jesús Banegas-Luna; Carlos Martinez-Cortes; Horacio Pérez Sánchez (CoRR, 2023)

ESSENCE-Dock: A Consensus-Based Approach to Enhance Virtual Screening Enrichment in Drug Discovery. - Jochem Nelen; Miguel Carmena-Bargueño; Carlos Martinez-Cortes; Alejandro Rodríguez-Martínez; José Manuel Villalgordo-Soto; Horacio Pérez Sánchez (J. Chem. Inf. Model., 2024)

Global and Local Interpretable Machine Learning Allow Early Prediction of Unscheduled Hospital Readmission. - Rafael Ruiz de San Martín; Catalina Morales-Hernández; Carmen Barberá; Carlos Martinez-Cortes; Antonio-Jesús Banegas-Luna; Francisco José Segura-Méndez; Horacio Pérez Sánchez; Isabel Morales-Moreno; Juan José Hernández Morante (Mach. Learn. Knowl. Extr., 2024)

Performance Impact of Containerized METADOCK 2 on Heterogeneous Platforms. - Antonio-Jesús Banegas-Luna; Baldomero Imbernón Tudela; Carlos Martinez-Cortes; José Maria Cecilia; Horacio Pérez Sánchez (CoRR, 2025)

WISCA: A Consensus-Based Approach to Harmonizing Interpretability in Tabular Datasets. - Antonio-Jesús Banegas-Luna; Horacio Emilio Pérez Sánchez; Carlos Martinez-Cortes (CoRR, 2025)