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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Published in | Nano biomedicine and engineering Vol. 14; no. 1; pp. 81 - 89 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
Tsinghua University Press
01.03.2022
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Subjects | |
Online Access | Get full text |
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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. |
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ISSN: | 2150-5578 2150-5578 |
DOI: | 10.5101/nbe.v14i1.p81-89 |