|本期目录/Table of Contents|

[1]苏淏璇,徐秀林△.深度学习在心电图分类中的应用分析*[J].生物医学工程研究,2020,04:419-424.
 SU Haoxuan,XU Xiulin.Application analysis of deep learning in electrocardiogram classification[J].Journal of Biomedical Engineering Research,2020,04:419-424.
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深度学习在心电图分类中的应用分析*(PDF)

《生物医学工程研究》[ISSN:1006-6977/CN:61-1281/TN]

期数:
2020年04期
页码:
419-424
栏目:
出版日期:
2020-12-25

文章信息/Info

Title:
Application analysis of deep learning in electrocardiogram classification
文章编号:
1372-3278(2020)04-0419-06
作者:
苏淏璇徐秀林△
上海理工大学医疗器械与食品学院,上海200093
Author(s):
SU Haoxuan XU Xiulin
School of Medical Instrument and Food Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China
关键词:
-
Keywords:
Deep learningElectrocardiogramNeural networksComputer-aided diagnosisReview
分类号:
R318
DOI:
10.19529/j.cnki.1672-6278.2020.04.18
文献标识码:
A
摘要:
深度学习;心电图;神经网络;计算机辅助诊断;综述
Abstract:
We summarize the latest research progress of deep learning in electrocardiogram(ECG) diagnostic applications, and elaborate the application examples of convolutional neural networks, recursive neural networks, deep belief networks,and deep residual networks.By comparing the ECG models based on different neural networks and analyzing the specific clinical applications of various computer-aided diagnosis models,we summarize the problems of deep learning in ECG diagnosis and the development trends in the future.

参考文献/References

备注/Memo

备注/Memo:
(收稿日期:2020-05-07)上海市科委科技支撑计划资助项目(19441904500)。△通信作者Email:xxlin100@163.com
更新日期/Last Update: 2021-02-07