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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Bibliografske podrobnosti
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
Drugi avtorji: School of Mechanical and Aerospace Engineering
Format: Journal Article
Jezik:English
Izdano: 2018
Teme:
Congestive Heart Failure
Convolutional Neural Network
DRNTU::Engineering::Electrical and electronic engineering
Online dostop:https://hdl.handle.net/10356/88148
http://hdl.handle.net/10220/45646

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