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

被引：0
|
作者：
Liang, Hanyang [1 ]
Zhang, Han [1 ]
Wang, Juan [1 ]
Shao, Xinghui [1 ]
Wu, Shuang [1 ]
Lyu, Siqi [1 ]
Xu, Wei [1 ]
Wang, Lulu [1 ]
Tan, Jiangshan [1 ]
Wang, Jingyang [1 ]
Yang, Yanmin [1 ]
机构：
[1] Chinese Acad Med Sci & Peking Union Med Coll, Natl Ctr Cardiovasc Dis, Natl Clin Res Ctr Cardiovasc Dis, Emergency Ctr,Fuwai Hosp,State Key Lab Cardiovasc, Beijing 100037, Peoples R China
来源：
REVIEWS IN CARDIOVASCULAR MEDICINE | 2024年 / 25卷 / 07期
关键词：
artificial intelligence; atrial fibrillation; machine learning; deep learning; MOBILE HEALTH TECHNOLOGY; RISK SCORE; PREDICTION; CARE; THROMBOEMBOLISM; RECURRENCE; MANAGEMENT; OUTCOMES; DIGOXIN; IMPACT;
D O I：
10.31083/j.rcm2507257
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
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.
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页数：13
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