Decision Support System for Heart Disease Diagnosis Using Interval Vague Set and Fuzzy Association Rule Mining

Abstract

The most common death is due to the condition that affects the heart is Cardiovascular disease (CVD). The inadequate oxygen to the heart leads to the symptoms like fatigue and chest pain (angina). This paper proposes a framework which incorporates the pre-processing step, Interval Vague set, Fuzzy Association Rule mining and Fuzzy Correlation rule mining for the decision making process. In this paper, the proposed framework mainly focused on the criteria that are causing the heart attack among the people. The pre-processing step is used to reduce the size of the heart disease dataset. Using the Rule Mining algorithm, the set of rules are generated for the prediction of heart diseases based on the selected criteria. Interval vague set is used to solve the decision making problem among the doctors regarding the heart disease among the patient who are in the hesitant state.