Heart Disease Prediction Using Deep Neural Network

Healthcare occupies an indispensable part in human lives. The healthcare industry contain large amount of psychiatric data hence machine learning models were used to provide conclusion effectively in the heart disease prediction. The classification of healthy person and non-healthy person can be done reliably by using machine learning methods. We developed a framework in this exploration that can understand the principles of predicting the risk profile of patients with the clinical data parameters. The proposed model is constructed using Deep Neural Network and χ
²
-statistical model. The problem of under fitting and over fitting is eliminated. This model shows better results on both the testing and training data. DNN and ANN were used to analyse the efficiency of the model which accurately predicts the presence or absence of heart disease.