ITI-IQA: a Toolbox for Heterogeneous Univariate and Multivariate Missing Data Imputation Quality Assessment. - Pedro Pons-Suñer; Laura Arnal; Jose Ramón Navarro-Cerdán; François Signol (CoRR, 2024)

A machine learning approach for type 2 diabetes diagnosis and prognosis using tailored heterogeneous feature subsets. - Jose Ramón Navarro-Cerdán; Pedro Pons-Suñer; Laura Arnal; Joaquim Arlandis; Rafael Llobet; Juan-Carlos Perez-Cortes; Francisco Lara-Hernández; Celeste Moya-Valera; Maria Elena Quiroz-Rodriguez; Gemma Rojo-Martinez; Sergio Valdés; Eduard Montanya; et al. (Medical Biol. Eng. Comput., 2025)

Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome. - Pedro Pons-Suñer; François Signol; Noemi Alvarez; Claudia Sargas; Sara Dorado; Jose Vicente Gil Ortí; Juan A. Delgado Sanchis; Marta Llop; Laura Arnal; Rafael Llobet; Juan-Carlos Perez-Cortes; Rosa Ayala; et al. (BMC Medical Informatics Decis. Mak., 2025)