Artificial intelligence for the detection, prediction, and management of atrial fibrillation; [Erkennung, Vorhersage und Behandlung von Vorhofflimmern mithilfe künstlicher Intelligenz]

被引：15
作者：
Isaksen J.L. [1 ]
Baumert M. [2 ]
Hermans A.N.L. [3 ]
Maleckar M. [4 ]
Linz D. [1 ,3 ]
机构：
[1] Department of Biomedical Sciences, University of Copenhagen, Copenhagen
[2] School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA
[3] Department of Cardiology, Maastricht University Medical Center and Cardiovascular Research Institute Maastricht, Maastricht
[4] Department of Computational Physiology, Simula Research Laboratory, Oslo
来源：
Herzschrittmachertherapie + Elektrophysiologie | 2022年 / 33卷 / 1期
关键词：
AF; AI; Deep learning; Disease management; Machine learning; Neural networks;
D O I：
10.1007/s00399-022-00839-x
中图分类号：
学科分类号：
摘要：
The present article reviews the state of the art of machine learning algorithms for the detection, prediction, and management of atrial fibrillation (AF), as well as of the development and evaluation of artificial intelligence (AI) in cardiology and beyond. Today, AI detects AF with a high accuracy using 12-lead or single-lead electrocardiograms or photoplethysmography. The prediction of paroxysmal or future AF currently operates at a level of precision that is too low for clinical use. Further studies are needed to determine whether patient selection for interventions may be possible with machine learning. © 2022, The Author(s).
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页码：34 / 41
页数：7
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