168615 20260211123813.0 doi 10.1007/s10489-025-07081-1 sideral 147956 ART-2026-147956 eng Trillo, José Ramón Universidad de Zaragoza (orcid)0000-0002-7998-5476 Explainable classifier with adaptive optimisation for medical data 2026 Artificial Intelligence (AI) has become increasingly important in critical domains such as medicine, where accurate and interpretable decision-making is essential. However, many high-performing AI models operate as “black boxes”, limiting transparency and making it difficult for clinicians to understand or verify predictions. To address this challenge, we present an eXplainable Artificial Intelligence (XAI) framework that integrates a fuzzy rule-based classifier with genetic algorithms and 2-tuple linguistic representations. The method incrementally generates general fuzzy rules, introduces fuzzy exception rules to capture atypical cases, and applies rule selection and parameter tuning to enhance both accuracy and interpretability. Experiments on nine medical datasets demonstrate that our approach achieves competitive or superior accuracy compared to state-of-the-art algorithms, while requiring fewer rules. These results show that the method not only improves predictive performance but also provides clear, human-readable explanations for each decision, thereby increasing trust and facilitating its application in medical practice. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/MICIU/PID2022-139297OB-I00 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Del Moral, María José Tapia, Juan Miguel García-Cabello, Julia Cabrerizo, Francisco Javier 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 56, 3 (2026), 77 [23 pp.] Appl. intell. APPLIED INTELLIGENCE 0924-669X 2815411 http://zaguan.unizar.es/record/168615/files/texto_completo.pdf Versión publicada 2250333 http://zaguan.unizar.es/record/168615/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:168615 articulos driver 2026-02-11-10:28:19 ARTICLE