使用视频喉腔镜与AI视觉辅助和没有AI视觉辅助进行内内腔管道输入性能比较:一个人偶试点研究
Georgiy Danylenko1, Sean D Jeffries1,2, Eric D Pelletier1
1From the Division of Surgical and Interventional Sciences, Department of Surgery, McGill University Health Center, Montreal, Quebec, Canada.
人工智能 (AI) 在视频喉腔镜 (VL) 中的视觉辅助显示了培训的潜力. 人工智能增强的VL (AI-VL) 提供了实时反,帮助初学者在程序期间保持关键观点.
科学领域:
- 医学技术 医学技术 医学技术
- 麻醉学 麻醉学
- 医学中的人工智能.
背景情况:
- 视频喉腔镜 (VL) 对于初学者来说是一个的学习曲线.
- 改善VL培训对于患者安全和程序效率至关重要.
研究的目的:
- 评估基于人工智能的视觉辅助在减少视频喉腔镜学习曲线方面的有效性.
- 评估人工智能增强的VL (AI-VL) 对未经验的志愿者的输管性能的影响.
主要方法:
- 招募了20名没有先前输管经验的志愿者.
- 参与者被随机分为两个组:标准VL和AI-VL.
- 每位参与者进行了10次连续的输入管,并记录了绩效指标.
主要成果:
- AI-VL组表明了对输管时间 (P > .05) 更的学习曲线的趋势.
- 人工智能系统充当虚拟教练,提供实时视觉反.
- 这种反有助于在输管过程中保持最佳的科尔马克-莱汉 (C-L) 视图.
结论:
- 基于AI的视觉辅助在VL中显示出作为训练工具的希望.
- AI-VL可能有助于加快技能获取,并改善新手用户的视图维护.
- 需要进一步的研究来证实AI-VL对临床结果的影响.
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