Artificial Intelligence for the Detection and Treatment of Atrial Fibrillation.

IF 2.6 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS
David M Harmon, Ojasav Sehrawat, Maren Maanja, John Wight, Peter A Noseworthy
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引用次数: 2

Abstract

AF is the most common clinically relevant cardiac arrhythmia associated with multiple comorbidities, cardiovascular complications (e.g. stroke) and increased mortality. As artificial intelligence (AI) continues to transform the practice of medicine, this review article highlights specific applications of AI for the screening, diagnosis and treatment of AF. Routinely used digital devices and diagnostic technology have been significantly enhanced by these AI algorithms, increasing the potential for large-scale population-based screening and improved diagnostic assessments. These technologies have similarly impacted the treatment pathway of AF, identifying patients who may benefit from specific therapeutic interventions. While the application of AI to the diagnostic and therapeutic pathway of AF has been tremendously successful, the pitfalls and limitations of these algorithms must be thoroughly considered. Overall, the multifaceted applications of AI for AF are a hallmark of this emerging era of medicine.

Abstract Image

Abstract Image

人工智能用于房颤的检测和治疗。
房颤是临床上最常见的心律失常,与多种合并症、心血管并发症(如卒中)和死亡率增加有关。随着人工智能(AI)不断改变医学实践,这篇综述文章重点介绍了人工智能在房颤筛查、诊断和治疗方面的具体应用。这些人工智能算法显著增强了常规使用的数字设备和诊断技术,增加了大规模人群筛查和改进诊断评估的潜力。这些技术同样影响了房颤的治疗途径,确定了可能从特定治疗干预中受益的患者。虽然人工智能在房颤诊断和治疗途径中的应用已经取得了巨大的成功,但必须彻底考虑这些算法的缺陷和局限性。总的来说,人工智能在房颤中的多方面应用是这个新兴医学时代的一个标志。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Arrhythmia & Electrophysiology Review
Arrhythmia & Electrophysiology Review CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
5.10
自引率
6.70%
发文量
22
审稿时长
7 weeks
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