Survey on Prediction of Heart Morbidity Using Data Mining Techniques

Abstract

Data mining is the non trivial extraction of implicit, previously unknown and potentially useful information from data. Data mining technology provides a user-oriented approach to novel and hidden patterns in the data. This paper presents about the various existing techniques, the issues and challenges associated with them. The discovered knowledge can be used by the healthcare administrators to improve the quality of service and also used by the medical practitioners to reduce the number of adverse drug effect, to suggest less expensive therapeutically equivalent alternatives. In this paper we discuss the popular data mining techniques namely, Decision Trees, Naïve Bayes and Neural Network that are used for prediction of disease.