A Novel Approach for Heart Disease Diagnosis using Data Mining and Fuzzy Logic

Cardiovascular disease is a term used to describe a variety of heart diseases, illnesses, and events that impact the heart and circulatory system. A clinician uses several sources of data and tests to make a diagnostic impression but it is not necessary that all the tests are useful for the diagnosis of a heart disease. The objective of our work is to reduce the number of attributes used in heart disease diagnosis that will automatically reduce the number of tests which are required to be taken by a patient. Our work also aims at increasing the efficiency of the proposed system. The observations illustrated that Decision Tree and Naive Bayes using fuzzy logic has outplayed over other data mining techniques.