实时人工智能对胃食道结合点山坡分类的前性评估
Ioannis Kafetzis1, Philipp Sodmann1, Bianca-Elena Herghelegiu1
1Interventional and Experimental Endoscopy (InExEn), Department of Internal Medicine 2, University Hospital Würzburg, Würzburg, Germany.
United European gastroenterology journal
|December 13, 2024
概括
与医生相比,一个人工智能 (AI) 系统在使用希尔分类对胃食道结 (GEJ) 的分类中表现出卓越的准确性. 这种人工智能工具有望提高诊断一致性,特别是对经验较少的内镜医生来说.
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:
- 在胃镜检查期间评估胃食道结 (GEJ) 的标准报告缺乏,影响了检查的一致性.
- 希尔分类为GEJ评估提供了一个标准化的方法.
- 这项研究解决了在GEJ文档中提高准确性和一致性的需求.
研究的目的:
- 为了比较人工智能 (AI) 系统与医生在使用希尔分类来分类GEJ的准确性.
- 评估人工智能系统在潜在的,盲目的优越性试验中的表现.
主要方法:
- 预计将131名患有完整的GEJ进行胃镜的患者纳入前性注册.
- 九名医生 (六名经验丰富,三名缺乏经验) 和人工智能系统实时评估了希尔等级.
- 三名独立的内镜专家的多数投票作为准确性评估的黄金标准.
主要成果:
- 人工智能系统实现了84.7%的显著更高的准确性,而医生的准确率为62.5% (p < 0.01).
- 在大多数希尔等级分类中,人工智能表现优于医生.
- 人工智能准确度明显优于缺乏经验的医生 (85%对56%,p < 0.01) 和趋势高于经验丰富的医生 (84%对69.6%,p = 0.07).
结论:
- 人工智能在评估GEJ的希尔分类方面明显超过了人类检查员.
- 人工智能系统的卓越性能为内镜医生提供了潜在的好处,特别是那些经验有限的人.
- 这项技术可以提高气镜中GEJ文档的标准化和可靠性.
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