Abstract
In this paper we present a fuzzy rule-based system to predict cardiovascularity diseases. The input variables of the system are the most in ffuent 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.
This research has been supported by CICYT PB98-1319
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Cordón, O., Herrera, F., de la Montaña, J., Sánchez, A., Villar, P. (2002). A Prediction System for Cardiovascularity Diseases Using Genetic Fuzzy Rule-Based Systems. In: Garijo, F.J., Riquelme, J.C., Toro, M. (eds) Advances in Artificial Intelligence — IBERAMIA 2002. IBERAMIA 2002. Lecture Notes in Computer Science(), vol 2527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36131-6_39
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DOI: https://doi.org/10.1007/3-540-36131-6_39
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