Diabetic Coronary heart disease is caused because of the plaque which block the flow of the blood inside the artery. The identification of this disease at the earlier stage could reverse the same and save valuable human life. To help in predicting it significantly Machine learning algorithm and Artificial Neural network (ANN) can play a major role. In this research work the machine learning algorithms ANN, Support Vector Machine (SVM) and Decision Tree (DT) are applied on the data consisting the various parameter causing the Diabetic Coronary heart disease. Two different datasets namely National Health and Nutrition Examination Survey (NHANES) and South Africa heart disease data are used for evaluation. A comparative analysis on all the three algorithms were carried out and in both the cases the highest accuracy in predicting the disease was produced by ANN.

Diabetic Coronary heart disease, Artificial Neural Network, Support Vector Machine, Decision Tree, Machine Learning