Saleh, EmranValls, AidaMoreno Pérez, AntonioRomero-Aroca, PedroTorra, VicençBustince Sola, Humberto2019-06-242020-09-16201810.1007/978-3-030-00202-2_10https://academica-e.unavarra.es/handle/2454/33478Comunicación presentada al 15th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2018 (15 - 18 october 2018).Fuzzy measures are used to express background knowledge of the information sources. In fuzzy rule-based models, the rule confidence gives an important information about the final classes and their relevance. This work proposes to use fuzzy measures and integrals to combine rules confidences when making a decision. A Sugeno $$\lambda $$ -measure and a distorted probability have been used in this process. A clinical decision support system (CDSS) has been built by applying this approach to a medical dataset. Then we use our system to estimate the risk of developing diabetic retinopathy. We show performance results comparing our system with others in the literature.13 p.application/pdfeng© Springer Nature Switzerland AG 2018, corrected publication 2018Aggregation functionsChoquet integralDiabetic retinopathyFuzzy measuresFuzzy rule-based systemsSugeno integralinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess