Decision Tree Driven Rule Induction for Heart Disease Prediction Model: Korean National Health and Nutrition Examinations Survey V-1

Abstract

Heart disease has the highest rates of death in non-communicable disease and there have been much research on heart disease. Even though there is recognition for importance of heart disease prediction, related studies are insufficient. Therefore, to develop heart disease prediction model for Korean, we suggest data mining driven rule induction for heart disease prediction in this paper. Proposed method suggest heart disease prediction model by applying decision tree driven rule induction based on data set from Korean National Health and Nutrition Examinations Survey V-1 (KNHANES V-1). The prediction model is expected contribute to Korea’s heart disease prediction.