The Application of Artificial Intelligence in Atrial Fibrillation Patients: From Detection to Treatment

Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although the guidelines for AF have been updated in recent years, its gradual onset and associated risk of stroke pose challenges for both patients and cardiologists in real-world practice. Artificial intelligence (AI) is a powerfu...

Full description

Saved in:
Bibliographic Details
Published inReviews in cardiovascular medicine Vol. 25; no. 7; p. 257
Main Authors Liang, Hanyang, Zhang, Han, Wang, Juan, Shao, Xinghui, Wu, Shuang, Lyu, Siqi, Xu, Wei, Wang, Lulu, Tan, Jiangshan, Wang, Jingyang, Yang, Yanmin
Format Journal Article
LanguageEnglish
Published Singapore IMR Press 01.07.2024
Subjects
artificial intelligence
atrial fibrillation
deep learning
machine learning
Review
deep learning
atrial fibrillation
machine learning
artificial intelligence
Online AccessGet full text

Cover

More Information
Summary:Atrial fibrillation (AF) is the most prevalent arrhythmia worldwide. Although the guidelines for AF have been updated in recent years, its gradual onset and associated risk of stroke pose challenges for both patients and cardiologists in real-world practice. Artificial intelligence (AI) is a powerful tool in image analysis, data processing, and for establishing models. It has been widely applied in various medical fields, including AF. In this review, we focus on the progress and knowledge gap regarding the use of AI in AF patients and highlight its potential throughout the entire cycle of AF management, from detection to drug treatment. More evidence is needed to demonstrate its ability to improve prognosis through high-quality randomized controlled trials.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ISSN:1530-6550
2153-8174
2153-8174
DOI:10.31083/j.rcm2507257