在心胸训练中使用人工智能手跟踪对手术技能的客观评估:一项可行性研究
M Atazadah1, M Bourass1, S A Max1
1Department of Cardiothoracic Surgery, Leiden University Medical Center, Leiden, Netherlands.
Interdisciplinary cardiovascular and thoracic surgery
|February 11, 2026
概括
基于人工智能 (AI) 的手跟踪客观地测量了外科技能,在预测外科经验方面表现优于传统方法. 将人工智能与传统工具相结合,为外科训练提供了最准确的评估.
科学领域:
- 外科教育的外科教育
- 医疗技术 医疗技术 医学技术
- 人工智能在医学中的应用
背景情况:
- 手术能力评估对于患者安全至关重要.
- 传统的评估工具往往依赖于主观的评估.
- 需要采取客观措施来加强外科培训.
研究的目的:
- 评估基于人工智能的手跟踪,以客观地评估外科技能.
- 为了比较人工智能手跟踪与预测手术经验的传统方法.
- 确定人工智能是否可以提高外科手术能力评估的准确性.
主要方法:
- 44名参与者完成了接和结节的任务.
- 使用人工智能跟踪软件分析了手的动作,以测量速度,长度和冲动.
- 线性回归模型使用程序时间,OSATS和手跟踪指标预测了经验年.
主要成果:
- 人工智能手部跟踪指标在新手和经验丰富的外科医生之间存在显著差异.
- 人工智能手指跟踪在预测多年的外科经验方面超过了传统工具 (调整后的R2为0.540-0.712与0.537-0.638).
- 将人工智能手跟踪与传统评估相结合,产生了最高的预测值 (R2调整为0.540-0.809).
结论:
- 基于人工智能的手跟踪提供客观和可重复的外科技能评估.
- 整合手部跟踪指标可以更好地预测手术经验.
- 人工智能支持在外科培训中进行标准化和客观的评估.
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