Detection of Coronary Heart Diseases using Data Mining Techniques

Abstract

In recent times, heart diseases have been prevalent throughout the globe. Millions of people die every year because of misdiagnosis of heart diseases. There is a dire need to develop correct diagnosis of heart related diseases based on data from earlier case scenarios.To aid early and correct diagnosis of these Coronary Heart Diseases, many data mining techniques have been devised using large amount of data available to the hospitals. The various algorithms devised are used to assist physicians in the diagnosis of heart diseases based on various patient parameters such as fasting blood sugar, previous heart events, age, etc. This paper analyses the best of these techniques which include the decision tree algorithm, the Naïve Bayes algorithm and the neural networks algorithm, and enlists the good and the bad in each one of them.