创建一个标准化工具,用于评估和比较基于人工智能的计算机辅助检测程序在结肠镜检查:一个修改的Delphi方法
Sanjay R V Gadi1, Yuichi Mori2, Masashi Misawa3
1Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
Gastrointestinal endoscopy
|November 28, 2024
概括
这项研究确定了评估结肠镜中计算机辅助检测 (CADe) 的关键指标. 最重要的标准包括灵敏度和独立验证,旨在改进结直肠癌查工具.
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:
- 计算机辅助检测 (CADe) 软件越来越多地用于结直肠癌查.
- 现有的CADe算法缺乏标准化的评估方法,在性能比较中产生不确定性.
- 在全球多个地区,CADe已经获得了监管批准.
研究的目的:
- 建立优先评分指标,用于评估和比较结肠镜中CADe算法.
- 开发一个基于共识的框架来评估在临床实践中CADe的性能.
主要方法:
- 一种经过修改的Delphi方法,涉及25名全球CADe专家进行结肠镜检查.
- 一个为期8个月的在线调查过程,包括标准生成,公开评论和多轮优先评分.
- 使用5分利克特级别排名121个最初生成的评分标准,改进到最后一组6.
主要成果:
- 对CADe算法的敏感性和单独/独立验证被确定为最优先的指标 (绑定).
- 腺瘤检测率,错误阳性率,延迟率和腺瘤错误率也被列为高优先级的评估标准.
- 该研究通过国际专家共识确定了6个关键指标.
结论:
- 这项研究提出了第一个关于在结肠镜中对CADe优先评分指标的国际共识.
- 确定的指标应指导CADe软件的开发和改进,以改善结直肠癌查.
- 未来的研究应该专注于使用基准数据集验证这些指标,以创建标准化的评分工具.
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