一个可解释的人工智能系统用于克罗恩氏病的识别和分级双气球肠镜图像的双气球肠镜图像
Qiuyuan Liu1, Wanqing Xie2, Aodi Wang2
1Department of Gastroenterology, First Affiliated Hospital of Anhui Medical University, Hefei, China.
United European gastroenterology journal
|July 3, 2025
概括
一个人工智能系统有助于从肠镜图像中识别和分类克罗恩病. 这种工具可以提高诊断的准确性和一致性,特别是对于经验较少的内镜医生来说.
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:
- 克罗恩氏病 (CD) 是一种慢性炎症状况,需要终身治疗.
- 诊断和管理CD经常遭受误诊和变化,特别是在初学者内镜医生.
- 开发了一个可解释的AI系统,以解决CD的诊断挑战.
研究的目的:
- 创建一个可解释的人工智能系统,使用双气球肠镜图像识别和分类克罗恩病.
- 该系统提供界限框本地化和因子特定分级解释,以提高可解释性.
- 通过人工智能驱动的分析改善克罗恩病评估性能.
主要方法:
- 基于YOLO-v5的算法被用来构建一个区域和分级模型,用于个别的.
- 该系统分析图像中的所有的预测结果,以进行临床解释.
- 数据集包括17036张用于培训/验证的图像和2018年图像的测试队列,其中包括9名内镜师参与的读者研究.
主要成果:
- 人工智能系统在克罗恩氏病检测方面实现了91.8%的灵敏度和0.949的AUC.
- 评估的尺寸,表面和深度的准确性分别为94.1%,92.5%和93.0%.
- 通过人工智能辅助,初级内镜师的灵敏度 (12.7%) 和严重性评估准确度 (26%) 和一致性 (27.4%) 提高了.
结论:
- 人工智能系统在识别和评估克罗恩氏病方面表现出专家水平的熟练程度,超过了一般内镜师.
- 该系统的透明决策过程有助于临床整合,增强内镜医生的信任和一致性.
- 这种人工智能工具为更准确,更可靠的克罗恩病诊断和管理提供了有希望的解决方案.
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