Pathological detection of the Coronary heart diseases through the technique of Data Mining

Abstract

In the modern times, heart diseases have become prevalent all over globe. Many people die every year because of the
wrong/misdiagnosis of these heart diseases. Therefore, a need to develop the correct diagnosis of the heart related
diseases, based on the data from the previous case scenarios is felt. So, to aid the early and precise diagnosis of
Coronary Heart Diseases, fewer data mining techniques are devised using the large amount of data available to
medical hospitals. Many algorithms devised are used to assist physicians in diagnosis of the heart diseases, based on
the different patient parameters like fasting blood sugar, previous heart events, age, etc. This research paper analyses
the various techniques which include decision tree algorithm, the Naive Bayes algorithm and neural networks
algorithm, and lists the good and bad in each and every one of them.