COMPETING DATA MINING METHODS USED FOR HEART DISEASE PREDICTION

Abstract

 Data Mining is a process of extracting the data from a large set of any raw data. Data Mining is one of the well-known technology that is used in the Health Organization. Data mining techniques plays an important role for the Prediction of the disease by which the health care professionals can diagnosis the diseases easily. Heart Disease is caused when the normal functionality of a heart is affected. There are various factors that affect the functionality of the heart. In this paper, the different data mining techniques are used to predict the heart disease. Data Mining techniques like Neural Network, Decision Tree and Naives Bayes Theorem are used. The main goal of this paper is to analyze the various data mining techniques used, comparing these techniques, to achieve the better accuracy of the techniques and to identify the risk level of the heart disease.