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中华心脏与心律电子杂志 ›› 2024, Vol. 12 ›› Issue (04) : 234 -238. doi: 10.3877/cma.j.issn.2095-6568.2024.04.007

综述

人工智能预测心脏性猝死和恶性心律失常风险研究进展
蔡铖1, 郦明芳1,()   
  1. 1.210029 南京,南京医科大学第一附属医院(江苏省人民医院)心血管内科
  • 收稿日期:2024-01-15 出版日期:2024-12-25
  • 通信作者: 郦明芳

Research progress of artificial intelligence in risk stratification of sudden cardiac death and malignant arrhythmias

Cheng Cai1, Mingfang Li1,()   

  1. 1.Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University (Jiangsu Province Hospital),Nanjing 210029, China
  • Received:2024-01-15 Published:2024-12-25
  • Corresponding author: Mingfang Li
引用本文:

蔡铖, 郦明芳. 人工智能预测心脏性猝死和恶性心律失常风险研究进展[J/OL]. 中华心脏与心律电子杂志, 2024, 12(04): 234-238.

Cheng Cai, Mingfang Li. Research progress of artificial intelligence in risk stratification of sudden cardiac death and malignant arrhythmias[J/OL]. Chinese Journal of Heart and Heart Rhythm(Electronic Edition), 2024, 12(04): 234-238.

心脏性猝死(SCD)仍是世界范围内重大公共卫生挑战,直接原因主要呈恶性心律失常。作为SCD 主要的预防和治疗措施,植入型心律转复除颤器设备昂贵,并且存在植入相关并发症风险,另外,根据目前临床指南需要植入的患者与发生SCD的高危人群并不完全重合。因此,临床上亟需更有效、可靠的SCD 风险预测模型。近年来,人工智能的发展为SCD 和恶性心律失常的预警开辟了新的道路。本文综述了该领域的最新研究进展,以期帮助读者熟悉相关研究内容并开拓研究思路。

表1 3个基于电子病历记录的心脏性猝死机器学习风险预测模型
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