人工智能辅助视频结肠镜用于性结肠炎的疾病监测:一项前性研究
Noriyuki Ogata1, Yasuharu Maeda1,2, Masashi Misawa1
1Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Kanagawa, Japan.
人工智能 (AI) 可以使用内镜评分来预测性结肠炎 (UC) 复发. 人工智能辅助结肠镜提高了非专家诊断的准确性,并有助于分层患者的复发风险.
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:
- 梅奥内镜子评分 (MES) 是评估性结肠炎 (UC) 活动的标准.
- 结肠镜中的人工智能 (AI) 旨在减少诊断变异性.
- 之前的研究没有评估AI能够预测临床复发或改善UC非专家的表现的能力.
研究的目的:
- 确定基于AI的MES分配是否可以预测UC患者的临床复发.
- 评估人工智能是否能提高非专业内镜师的诊断性能.
- 评估AI对MES评分中观察者间和观察者内部变异性的影响.
主要方法:
- 一项前性队列研究,对110名UC患者进行了缓解.
- 开发一种人工智能算法,使用来自898名患者的74,713张结肠镜图像.
- 12个月的随访以确定临床复发 (部分梅奥得分>2) 和124个视频的多读者分析.
主要成果:
- 基于AI的MES得分为1预测了明显更高的复发率 (24.5%),而得分为0 (3.2%).
- 基于AI的MES为2或3的患者的复发率为50%,而得分为0或1的患者的复发率为16.2%.
- 与单独的内镜师相比,人工智能证明了观察者之间的和观察者内部的可再生性得到了改善.
结论:
- 人工智能辅助结肠镜可以有效地分层UC患者的临床复发风险.
- 基于人工智能的MES系统提高了非专业内镜师的诊断准确度.
- 人工智能在结肠镜检查中的整合显示了改善UC管理的前景.
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