Combining convolutional neural network and distance distribution matrix for identification of congestive heart failure
Congestive heart failure (CHF) is a serious pathophysiological condition with high morbidity and mortality, which is hard to predict and diagnose in early age. Artificial intelligence and deep learning combining with cardiac rhythms and physiological time series provide a potential to help in solvin...
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Main Authors: | Li, Yaowei, Zhang, Yao, Zhao, Lina, Zhang, Yang, Liu, Chengyu, Zhang, Li, Zhang, Liuxin, Li, Zhensheng, Wang, Binhua, Ng, Eyk, Li, Jianqing, He, Zhiqiang |
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其他作者: | School of Mechanical and Aerospace Engineering |
格式: | Article |
語言: | English |
出版: |
2018
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主題: | |
在線閱讀: | https://hdl.handle.net/10356/88148 http://hdl.handle.net/10220/45646 |
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機構: | Nanyang Technological University |
語言: | English |
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