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...

詳細記述

書誌詳細
主要な著者: Li, Yaowei, Zhang, Yao, Zhao, Lina, Zhang, Yang, Liu, Chengyu, Zhang, Li, Zhang, Liuxin, Li, Zhensheng, Wang, Binhua, Ng, Eyk, Li, Jianqing, He, Zhiqiang
その他の著者: School of Mechanical and Aerospace Engineering
フォーマット: Journal Article
言語:English
出版事項: 2018
主題:
Congestive Heart Failure
Convolutional Neural Network
DRNTU::Engineering::Electrical and electronic engineering
オンライン･アクセス:https://hdl.handle.net/10356/88148
http://hdl.handle.net/10220/45646

インターネット

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

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