A hybrid genetic-fuzzy expert system for effective heart disease diagnosis

Abstract

This paper presents a genetic algorithm (GA)-based fuzzy logic approach for computer aided disease diagnosis scheme. The aim is to design a fuzzy expert system for heart disease diagnosis. The designed system is based on Cleveland Heart Disease database. Originally there were thirteen attributes involved in predicting the heart disease. In this work genetic algorithm is used to determine the attributes that contribute more towards the diagnosis. Thirteen attributes are reduced to six attributes using genetic search. Fuzzy expert system is used for developing knowledge based systems in medicine. The proposed system uses Mamdani inference method. The system designed in Matlab software can be viewed as an alternative for existing methods to distinguish of heart disease presence. © 2011 Springer-Verlag.