Hanyang Liang, Han Zhang, Juan Wang, Xinghui Shao, Shuang Wu, Siqi Lyu, Wei Xu, Lulu Wang, Jiangshan Tan, Jingyang Wang, Yanmin Yang
{"title":"人工智能在心房颤动患者中的应用:从检测到治疗","authors":"Hanyang Liang, Han Zhang, Juan Wang, Xinghui Shao, Shuang Wu, Siqi Lyu, Wei Xu, Lulu Wang, Jiangshan Tan, Jingyang Wang, Yanmin Yang","doi":"10.31083/j.rcm2507257","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11317345/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Application of Artificial Intelligence in Atrial Fibrillation Patients: From Detection to Treatment.\",\"authors\":\"Hanyang Liang, Han Zhang, Juan Wang, Xinghui Shao, Shuang Wu, Siqi Lyu, Wei Xu, Lulu Wang, Jiangshan Tan, Jingyang Wang, Yanmin Yang\",\"doi\":\"10.31083/j.rcm2507257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":20989,\"journal\":{\"name\":\"Reviews in cardiovascular medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11317345/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Reviews in cardiovascular medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.31083/j.rcm2507257\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reviews in cardiovascular medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.31083/j.rcm2507257","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
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 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.
期刊介绍:
RCM is an international, peer-reviewed, open access journal. RCM publishes research articles, review papers and short communications on cardiovascular medicine as well as research on cardiovascular disease. We aim to provide a forum for publishing papers which explore the pathogenesis and promote the progression of cardiac and vascular diseases. We also seek to establish an interdisciplinary platform, focusing on translational issues, to facilitate the advancement of research, clinical treatment and diagnostic procedures. Heart surgery, cardiovascular imaging, risk factors and various clinical cardiac & vascular research will be considered.