人工智能用于对外科手术期间心肌缺血的心电图诊断:一个范围审查
Anne Kim1, Mitchell Chatterjee2, Alla Iansavitchene3
1Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.
British journal of anaesthesia
|July 4, 2025
概括
人工智能 (AI) 在通过清洁心电图 (ECG) 来检测心肌缺血时表现出高准确度. 然而,人工智能算法需要对杂的周围手术数据进行测试,以便在现实世界中临床使用.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 周术心电图 (ECG) 监测辅助器用于检测心肌缺血症.
- 当前的应用程序面临着虚假报警和信号污染的挑战.
- 人工智能 (AI) 正在探索术后心电图解释.
研究的目的:
- 进行关于人工智能在外科手术期间心电图解释当前状态的范围审查.
- 确定人工智能算法的有效性和局限性,以检测心肌缺血.
主要方法:
- 在主要数据库 (Ovid MEDLINE,EMBASE,Compendex,CINAHL) 进行了全面的文献搜索,截至2023年5月10日.
- 包括专注于心肌缺血或心脏梗塞ECG监测的原始研究文章.
- 分析了1991年至2023年间发表的182篇研究文章.
主要成果:
- 大多数人工智能算法 (132项研究) 都是通过使用现有的心电图数据库来追溯开发的.
- 在58%的研究中使用信号处理过器来减轻噪音.
- 在清洁数据上,ResNet算法实现了高中位灵敏度 (98.4%),精度 (99.8%) 和特异性 (99.1%).
结论:
- 人工智能在清洁的心电图数据中显示了对心肌缺血检测的高诊断准确性.
- 在干净的数据库上开发的算法在杂的周围操作环境中缺乏验证.
- 对于在现实世界中测试的AI算法,需要进一步的研究,噪音较大的周围操作和远程监控环境.
关键词:
这是一个ECGECGECGECGECG.人工智能是一种人工智能.电心电图 (ECG) 是一种心电图.机器学习是机器学习.监控 监控 监控 监控 监控 监控心肌梗塞的心脏病发作心肌缺血症是什么心肌缺血症远程家用监控 远程家用监控更多相关视频
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