Deep Neural Networks for Prediction of Card-iovascualr Diseases

In recent years, a huge extent of data that contains hidden information is collected by the health care industries. Deep Neural Networks (DNN) have been employed to obtain appropriate decisions and effective results. The obtained results have been validated using confusion matrix and region of inter...

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Bibliographic Details
Published inNano biomedicine and engineering Vol. 14; no. 1; pp. 81 - 89
Main Authors Muhammad Aqeel Aslam, Muhammad Asif Munir, Rauf Ahmad, Muhammad Samiullah, Nasir Mahmood Hassan, Shahzadi Mahnoor, Daxiang Cui
Format Journal Article
LanguageEnglish
Published Tsinghua University Press 01.03.2022
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Summary:In recent years, a huge extent of data that contains hidden information is collected by the health care industries. Deep Neural Networks (DNN) have been employed to obtain appropriate decisions and effective results. The obtained results have been validated using confusion matrix and region of interest. In this work, we have used fourteen parameters for the prediction of cardiovascular disease (CVD) of 303 volunteers. The proposed predictive technique predicts that the chance for prediction of the risk level of cardiovascular disease. In this work, the prediction method using deep neural networks showed the highest accuracy. Our proposed method has outperformed the existing methods and can be combined with multimedia technology.
ISSN:2150-5578
2150-5578
DOI:10.5101/nbe.v14i1.p81-89