对使用人工智能在冠状动脉内光学连贯性断层扫描分析中的审查和建议
Xu Chen1, Yuan Huang1,2, Benn Jessney1
1Department of Medicine, University of Cambridge, Puddicombe Way, Cambridge CB2 0AW, UK.
European heart journal. Digital health
|July 24, 2025
概括
人工智能 (AI) 工具显示出使用血管内光学连贯断层扫描 (IVOCT) 图像诊断冠状动脉疾病 (CAD) 的前景. 然而,目前大多数人工智能模型由于缺陷而缺乏临床实用性,需要改进研究实践.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 从血管内光学连贯断层扫描 (IVOCT) 图像提供了诊断冠状动脉疾病 (CAD) 的潜力.
- 使用IVOCT进行CAD诊断的现有AI模型需要严格的验证才能获得临床应用.
研究的目的:
- 系统地审查基于人工智能的CAD诊断模型,使用IVOCT.
- 评估这些AI模型的临床实用性和验证状态.
- 为改善人工智能模型质量和研究实践提供建议.
主要方法:
- 对2015年1月至2024年12月期间发表的研究进行系统性文献综述.
- 搜索发现了8600项研究;在初始查后,包括了629项研究.
- 在质量评估后的最终审查中包括了39项研究.
主要成果:
- 大多数审查的AI模型目前不适合临床使用.
- 方法上的缺陷和潜在的偏见被确定为主要限制.
- 在用于CAD诊断的AI模型的验证中存在显著的变异性.
结论:
- 目前用于基于IVOCT的CAD诊断的AI模型需要大幅改进.
- 提供了建议,以加强模型开发和研究实践.
- 未来的努力应该集中在严格的验证上,以确保AI工具的临床实用性.
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