In this paper we present a fuzzy rule-based system to predict cardiovascularity diseases. The input variables of the system are the most influent factors for that type of diseases and the output is a risk prediction of suffering from them. Our objective is to get an accurate prediction value and a system description with a high degree of interpretability. We use a set of examples and a design process based on genetic algorithms to obtain the components of the fuzzy rule-based system.
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