Heart disease is one of the major diseases threatening human health. This paper proposed a novel deep neural network model to predict heart disease based on routine clinical data. We adapt the deep residual structure to discover a novel Deep Residual Neural Network (DRNN). In order to verify the effectiveness of DRNN, we performed experiments on Heart Disease UCI. The accuracy reached 95%, which is better than the traditional machine learning methods among Random Forest 83%, Decision Tree 68%, Logistic Regression 87%, KNN 60%, Native Bayes 80%.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.