Predictive Analysis for the Diagnosis of Coronary Artery Disease using Association Rule Mining

Abstract

In this paper, we present an improved association rule mining of data mining for the detection of Coronary Artery Disease (CAD). The whole concept behind the research is carried out by using a heart disease database, which is collected from different locations and from different patients. It is actually collected from 303 random visitors to Tehran's Shaheed Rajaei Cardiovascular, Medical and Research Centre. The mechanism proposed in this article uses the same heart disease database as input and apply the improved association rule mining method to identify the decision rules with the correctness and robustness. This paper shows conclusions of our proposed work and results.