Research Article Open Access

Performance of Decision Trees for Assessment of the Risk Factors of Heart Disease

Abstract

Coronary heart disease refers to the failure of coronary circulation to supply adequate circulation to cardiac muscle and surrounding tissue. The events myocardial infarction (MI), percutaneous coronary intervention (PCI), and coronary artery bypass graft surgery (CABG) were investigated The risk factors investigated were: 1) before the event: a) no modifiable—age, sex, and family history for premature CHD, b) modifiable—smoking before the event, history of hypertension, and history of diabetes; and 2) after the event: modifiable—smoking after the event, systolic blood pressure, diastolic blood pressure, total cholesterol, high- density lipoprotein, low-density lipoprotein, triglycerides, and glucose.. Data-mining analysis was carried out using the C5 decision tree algorithm for the aforementioned three events using five different splitting criteria. C4.5 is a widely-used free data mining tool that is descended from an earlier system called ID3 and is followed in turn by C5.0. It embodies new algorithms for generating rule sets, and the improvement is dramatic in accuracy, speed and memory.

Dr.K.P.Kaliyamurthie, D.Parameswari

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