Risk Prediction of Ischemic Heart Disease Using Artificial Neural Network

The fatty plaque deposits narrow artery walls leading to the heart Ischemic Heart Disease (IHD). For that, the flowing of blood is reduced. Hyperpiesia polygenic disorder, drug addiction, and lipidemia are the initiators of tachycardia. From the healthcare unit, 835 IHD patients data with 14 features like Age, Sex, Diabetes Mellitus (DM), Electrocardiograph (ECG), Exercise Tolerance Test (ETT) etc. have been collected. By implementing artificial neural network (ANN) techniques in our collected dataset the risk prediction is determined around 84.47%. The precision, sensitivity, specificity, and fl-score, for the ANN, are 79.97, 82.69, 72.63, and 85.17 respectively. The significant contingency of tachycardia is anticipated.