验证人工智能计算机辅助检测在结肠镜检查中的结肠瘤
Hannah Lee1, Jun-Won Chung1, Kyoung Oh Kim1
1Division of Gastroenterology, Department of Internal Medicine, Gachon University Gil Medical Center, Incheon 21565, Republic of Korea.
Diagnostics (Basel, Switzerland)
|December 17, 2024
概括
这项研究验证了ALPHAON®人工智能 (AI) 计算机辅助检测 (CADe) 算法用于结肠多体检测. 人工智能系统向专家内镜师展示了优越的性能,并提高了专家和学员的检测率.
科学领域:
- 胃肠病学 胃肠病学
- 医疗成像医学成像
- 人工智能在医学中的应用
背景情况:
- 结肠镜质量对于检测结肠片至关重要,从而降低结肠直肠癌风险.
- 人工智能 (AI) 越来越多地被用于医疗学科.
- 此前,ALPHAON®计算机辅助检测 (CADe) 算法已被开发用于聚合物识别.
研究的目的:
- 为了验证ALPHAON® AI CADe算法用于结肠多胞体检测.
- 将ALPHAON®的诊断性能与专家内镜师进行比较.
- 评估人工智能对内镜师的多重体检测能力的影响.
主要方法:
- 500张静止结肠图像 (100个多,400个健康) 的回顾性分析.
- 验证ALPHAON® CADe算法的诊断性能.
- 与两名专家内镜师和六名实习生进行比较,在洗期后有或没有人工智能协助.
主要成果:
- ALPHAON® CADe算法实现了高检测精度 (0.97),灵敏度 (0.91),特异性 (0.99),以及AUC (0.967).
- 在精度,灵敏度和特异性方面,ALPHAON®的表现优于专家内镜师.
- 人工智能协助显著提高了专家和实习内镜师的多检测能力.
结论:
- 在结肠镜检查期间,ALPHAON® CADe系统在检测结肠杆菌中表现出高性能.
- ALPHAON®的优越灵敏度表明它有可能超过专家内镜医生.
- 该算法有效地增强了新手和经验丰富的内镜师的聚检测,表明其作为内镜助手的价值.
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