Machine Learning for Detecting Atrial Fibrillation from ECGs: Systematic Review and Meta-Analysis

Machine Learning for Detecting Atrial Fibrillation from ECGs: Systematic Review and Meta-Analysis

Background: Atrial fibrillation (AF) is a common arrhythmia that can result in adverse cardiovascular outcomes but is often difficult to detect. The use of machine learning (ML) algorithms for detecting AF has become increasingly prevalent in recent years. This study aims to systematically evaluate...

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Bibliographic Details
Main Authors: Chenggong Xie, Zhao Wang, Chenglong Yang, Jianhe Liu, Hao Liang
Format: Article
Language:English
Published: IMR Press 2024-01-01
Series:Reviews in Cardiovascular Medicine
Subjects:
machine learning
atrial fibrillation
ecg
meta-analysis
Online Access:https://www.imrpress.com/journal/RCM/25/1/10.31083/j.rcm2501008

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