Deep Neural Network Based Cardio Vascular Disease Prediction Using Binarized Butterfly Optimization

In this digital era, Cardio Vascular Disease (CVD) has become the leading cause of death which led to mortality 17.9 million lives each year. Earlier Diagnosis people who are at higher risk CVDs helps them receive proper treatment and prevent deaths. It becomes inevitable propose a solution predict CVD with high accuracy. A system for predicting using Deep Neural Network Binarized Butterfly Optimization Algorithm (DNN–BBoA) is proposed. The BBoA incorporated select best features. optimal features fed deep neural network classifier it improves prediction accuracy reduces time complexity. usage further improve minimal proposed tested two datasets namely Heart disease dataset from UCI repository Kaggle Repository. work compared different machine learning classifiers such as Support Vector Machine, Random Forest, Decision Tree Classifier. DNN–BBoA 99.35% heart data set yielding an 80.98% cardiovascular dataset.