Intelligent heart disease prediction system using random forest and evolutionary approach

Abstract

Heart disease is a leading cause of premature death in the world.Predicting the outcome of disease is the challenging task.Data mining is involved to automatically infer diagnostic rules and help specialists to make diagnosis process more reliable.Several data mining techniques are used by researchers to help health care professionals to predict the heart disease.Random forest is an ensemble and most accurate learning algorithm,suitable for medical applications.Chi square feature selection measure is used to evaluate between variables and determines whether they are correlated or not.In this paper ,we propose a classification model which uses random forest as classifier ,chi square and genetic algorithm as feature selection measures to predict heart disease. The experimental results have shown that our approach improve classification accuracy compared to other classification approaches,and the presented model can be successfully used by health care professional for predicting heart disease.