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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Bibliographic Details
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
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2018
Subjects:
Congestive Heart Failure
Convolutional Neural Network
DRNTU::Engineering::Electrical and electronic engineering
Online Access:https://hdl.handle.net/10356/88148
http://hdl.handle.net/10220/45646

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