人工智能和内镜师对多体特征的准确性:在第三级内镜中心进行的一项前性,非随机化研究
Sebastian Baumer1, Kilian Streicher1, Saleh A Alqahtani2,3
1Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany.
Endoscopy international open
|September 20, 2023
概括
这项研究评估了一种新的人工智能 (AI) 系统,用于分类结肠多. 人工智能显示出高准确性,但在临床实践中没有满足"删除和丢弃"策略的标准.
科学领域:
- 胃肠病学 胃肠病学
- 医疗人工智能 医疗人工智能
- 内視鏡診斷診斷 內視鏡診斷診斷
背景情况:
- 人工智能 (AI) 在胃肠内镜领域正在迅速发展.
- 计算机辅助检测 (CAD) 和诊断 (CADx) 系统正在成为可用的.
- 这项研究评估了一个新的商业AI CADx系统的现实世界诊断性能.
研究的目的:
- 评估一种新型人工智能系统的诊断准确度,用于表征结直肠多.
- 将AI的性能与内镜分类进行比较.
- 确定人工智能是否符合"删除和丢弃"策略的标准.
主要方法:
- 在学术内镜中心进行前性非随机研究 (2022年3月至8月).
- 156名患者接受了结肠镜检查,并为262个多重体 (≤10毫米) 进行了多重切除术.
- 同时通过内镜和AI系统进行检查;AI对瘤与非瘤息肉的分类准确度是主要结果.
主要成果:
- 人工智能系统实现了89.70%的灵敏度,75.26%的特异性和84.35%的准确性.
- 内镜师的精度因经验而异,经验较少的内镜师显示95.56%的灵敏度,61.54%的特异性和83.10%的精度.
- 经验丰富的内镜师表现出90.83%的灵敏度,71.83%的特异性和83.77%的准确性.
结论:
- 评估的人工智能系统显示了高精度的多体的特征.
- 然而,它的表现目前还不符合"删除和丢弃"战略所需的严格标准.
- 在这种情况下,需要进一步的验证和潜在的改进才能在临床采用.
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