在心血管疾病管理中利用人工智能:承诺与现实对比
Sebastian E Beyer1, Paweł T Matusik2,3, Leon M Ptaszek4
1Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, Massachusetts, United States.
Kardiologia polska
|January 15, 2026
概括
人工智能 (AI) 可以通过检测复杂的数据模式来增强心血管医学. 这篇评论探讨了现代人工智能,将其与传统的机器学习进行比较,并讨论了AI评估指标和临床使用的局限性.
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:
- 人工智能 (AI) 通过微妙的数据模式检测,有望改善心血管医学.
- 人工智能技术的快速发展给评估基于人工智能的决策支持工具的临床医生带来了挑战.
- 许多AI算法正在为心血管应用开发.
研究的目的:
- 在心血管医学中提供现代人工智能模型的概述.
- 将现代AI方法与传统的机器学习方法进行比较.
- 讨论评估AI性能和局限性的关键指标.
主要方法:
- 对现代人工智能模型和传统机器学习技术的文献综述.
- 对评估人工智能模型性能指标的分析.
- 讨论关键的人工智能局限性,包括偏见,概括性和可解释性.
主要成果:
- 现代人工智能模型为心血管数据中的模式识别提供了先进的功能.
- 比较突出了当代人工智能和既定机器学习方法之间的差异.
- 确定了关键的绩效指标和AI在临床环境中的重大局限性.
结论:
- 人工智能具有显著的潜力,可以提高心血管医学中的患者护理.
- 由于技术的快速发展,临床医生需要一个框架来批判性地评估AI工具.
- 解决人工智能的局限性,如偏见和缺乏可解释性,对于安全有效的临床实施至关重要.
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