Liang Hanyang, Zhang Han, Wang Juan, Shao Xinghui, Wu Shuang, Lyu Siqi, Xu Wei, Wang Lulu, Tan Jiangshan, Wang Jingyang, Yang Yanmin
Emergency Center, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease of China, National Center for Cardiovascular Diseases, National Clinical Research Center of Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, 100037 Beijing, China.
Rev Cardiovasc Med. 2024 Jul 10;25(7):257. doi: 10.31083/j.rcm2507257. eCollection 2024 Jul.
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.
心房颤动（AF）是全球最常见的心律失常。尽管近年来AF指南已更新，但其逐渐发作以及相关的中风风险在实际临床实践中给患者和心脏病专家都带来了挑战。人工智能（AI）是图像分析、数据处理以及建立模型方面的强大工具。它已广泛应用于包括AF在内的各个医学领域。在本综述中，我们聚焦于AF患者中使用AI的进展和知识空白，并强调其在AF管理的整个周期（从检测到药物治疗）中的潜力。需要更多证据通过高质量随机对照试验来证明其改善预后的能力。
