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Deep Neural Network Based Cardio Vascular Disease Prediction Using binarized butterfly optimization

Intelligent Automation & Soft Computing 2023年第5期36卷 1863-1880页

作者： S.Amutha J.Raja Sekar Department of Computer Science and Engineering Mepco Schlenk Engineering College(Autonmous)SivakasiIndia

In this digital era,Cardio Vascular Disease(CVD)has become the lead-ing cause of death which has led to the mortality of 17.9 million lives each *** Diagnosis of the people who are at higher risk of CVDs helps them to receive proper treatment and helps prevent *** becomes inevitable to pro-pose a solution to predict the CVD with high accuracy.A system for predicting Cardio Vascular Disease using Deep Neural Network with binarized butterﬂy optimization algorithm(DNN–BBoA)is *** BBoA is incorporated to select the best *** optimal features are fed to the deep neural network classiﬁer and it improves prediction accuracy and reduces the time *** usage of a deep neural network further helps to improve the prediction accu-racy with minimal *** proposed system is tested with two datasets namely the Heart disease dataset from UCI repository and CVD dataset from Kag-gle *** proposed work is compared with different machine learning classiﬁers such as Support Vector Machine,Random Forest,and Decision Tree Classiﬁ*** accuracy of the proposed DNN–BBoA is 99.35%for the heart dis-ease data set from UCI repository yielding an accuracy of 80.98%for Kaggle repository for cardiovascular disease dataset.

关键词： Deep neural network cardio vascular disease binarized butterﬂy optimization algorithm feature selection

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