一个人工智能驱动的评分系统,用于测量性结肠炎中组织学疾病活性
Laurent Peyrin-Biroulet1, Shashi Adsul2, Andrea Stancati2
1Department of Gastroenterology, INFINY Institute, FHU-CURE, INSERM NGERE, Nancy University Hospital, Vandoeuvre-lès-Nancy, France.
一个人工智能 (AI) 系统使用南希指数准确地测量了性结肠炎 (UC) 中的组织学疾病活性. 这种人工智能工具对降低可变性和改善炎症性肠道疾病的临床应用充满希望.
科学领域:
- 组织病理学 组织病理学
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 在性结肠炎 (UC) 中,组织学图像评估受到观察者变异性的影响.
- 开发客观的评分方法对于一致的疾病评估至关重要.
研究的目的:
- 根据南希指数,评估AI系统在UC中测量组织学疾病活动的能力.
- 评估人工智能驱动和基于病理学家的南希指数得分之间的相关性.
主要方法:
- 开发了一种利用深度学习和特征提取的新型AI算法.
- 200张UC组织图像由四名病理学家和AI工具分析.
- 类内相关系数 (ICC) 用于评估手动和人工智能测量之间的一致性.
主要成果:
- 人工智能工具与组织病理学家的评估有很高的相关性.
- 组织病理学家之间的平均ICC为89.3,组织病理学家和AI工具之间的平均ICC为87.2.2.
- 人工智能系统实现了南希指数的准确测量.
结论:
- 人工智能方法显示出在炎症性肠病中临床应用的巨大潜力.
- 由人工智能驱动的自动化评分系统可以提高客观性,减少资源使用,并在日常实践中帮助治疗决策.
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