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人工神经网络与心电图解读:应用与滥用

Artificial neural networks and ECG interpretation. Use and abuse.

作者信息

Dassen W R, Mulleneers R G, den Dulk K, Talmon J L

机构信息

Department of Cardiology, University of Limburg, Maastricht, The Netherlands.

出版信息

J Electrocardiol. 1993;26 Suppl:61-5.

PMID:8189149
Abstract

The computerized interpretation of the resting electrocardiogram has reached a steady-state phase: an equilibrium between sensitivity and specificity has been reached. New computer techniques, such as expert systems and artificial neural network technology, have been proposed or are currently under evaluation. Although neural network techniques are based on complex mathematical theories and their application is full of pitfalls, progress has been made in a number of subdomains, like signal filtering, electrocardiographic classification, and compression of stress electrocardiograms. Presently, the hesitating acceptance by the human user forms one of the obstacles that needs to be overcome by convincing, well-performed studies.

摘要

静息心电图的计算机化解读已进入稳态阶段

在敏感性和特异性之间已达成平衡。诸如专家系统和人工神经网络技术等新的计算机技术已被提出或正在接受评估。尽管神经网络技术基于复杂的数学理论且其应用充满陷阱,但在一些子领域已取得进展,如信号滤波、心电图分类以及运动心电图的压缩。目前,人类用户的迟疑接受是需要通过令人信服的、执行良好的研究来克服的障碍之一。

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Artificial neural networks and ECG interpretation. Use and abuse.人工神经网络与心电图解读:应用与滥用
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PLoS One. 2017 Oct 3;12(10):e0182500. doi: 10.1371/journal.pone.0182500. eCollection 2017.