Comparative Study on Heart Disease Prediction System Using Data Mining Techniques

T. Revathi, S. Jeevitha

Abstract: Healthcare industry has huge amount of data that contains hidden information. This information supports decision making process on related area. In this research paper, we discussed various approaches of data mining which are useful in predicting the heart disease. One of the complex tasks in healthcare industry is predicting of heart disease and it requires more experience and knowledge. Some of the ways of predicting heart diseases are ECG, stress test and heart MRI etc. Here the system uses 14 parameters for predicting heart disease that include blood pressure, cholesterol, chest pain and heart rate. These parameters are used to improve an accuracy level. The main aim of this paper is to provide an analysis of data mining techniques on diagnosing heart disease.

Keywords: Heart disease, Neural Network, Nave bayes and Decision tree