The Role of Diabetes Mellitus in Prediction of Myocardial Infarction using CHAID based Data Mining Model

Abstract

The Classifiers are the mechanism to predict the possibilities of existence of the given data called test data with the collection of known values called trained data through machine learning. This paper is an attempt to identify the causative factor of diabetic’s mellitus influencing Myocardial Infarction using most promising Classifier CHAID (Chi Square Automatic Interaction Detection) and also find its classification efficiency. The diabetes mellitus has a prominent role in causing Myocardial Infarction to human in most of the cases. Besides that the relevant parameters such as body mass index, fast blood sugar, varying hemoglobin, high density lipids, low density lipids, triglycerides, systolic blood pressure, diastolic blood pressure, and nicotine usage, etc seems to influence the occurrence of Myocardial Infarction were significantly showed by CHAID classifiers.