Combining convolutional neural network and distance distribution matrix for identification of congestive heart failure

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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Detalles Bibliográficos
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
Outros autores: School of Mechanical and Aerospace Engineering
Formato: Journal Article
Idioma:English
Publicado: 2018
Subjects:
Congestive Heart Failure
Convolutional Neural Network
DRNTU::Engineering::Electrical and electronic engineering
Acceso en liña:https://hdl.handle.net/10356/88148
http://hdl.handle.net/10220/45646

Internet

https://hdl.handle.net/10356/88148
http://hdl.handle.net/10220/45646

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