白光电脑辅助光学诊断微小结直肠息肉在常规临床实践中
Emanuele Rondonotti1, Irene Maria Bambina Bergna2,1,3, Silvia Paggi1
1Gastroenterology Unit, Valduce Hospital, Como, Italy.
Endoscopy international open
|May 22, 2024
概括
人工智能 (AI) 可以通过高灵敏度但低特异性来诊断小结直肠多 (DCP). 人工智能辅助的光学诊断 (OD) 提高了准确性,特别是对于专家内镜医生来说,提高了实时的息肉分类.
科学领域:
- 胃肠病学 胃肠病学
- 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) 提供了客观光学诊断 (OD) 的潜力减小结直肠多体 (DCPs).
- 人工智能系统在OD中的现实世界的可行性和诊断性能正在调查中.
研究的目的:
- 用白光系统来前性评估AI独立和AI辅助的DCP的OD.
- 评估人机交互对实时结肠镜诊断性能的影响.
主要方法:
- 11名内镜师 (5名专家,6名非专家) 评估了480个DCP.
- 人工智能独立的OD和人工智能辅助的OD与组织病理学作为黄金标准进行了比较.
主要成果:
- 人工智能独立的OD实现了81.4%的分类率,具有97.0%的灵敏度和38.1%的特异性.
- 人工智能辅助的OD显著提高了特异性 (58.9%) 和整体准确性 (专家为85.8%).
- 人机交互增强了诊断性能,尤其是专家内镜医生.
结论:
- 人工智能独立的OD为DCPs提供了高灵敏度但有限的特异性.
- 人工智能辅助的OD提高了实时片检测的诊断准确性和可靠性.
- 专家内镜师从人工智能协助中获益最多,强调了人机协作的价值.
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