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数字细胞学与人工智能相结合,与用于囊细胞学的传统显微镜相比:初步研究
Renê Gerhard1, Cioly Rivero Colmenarez1, Corinne Selle1
1Centre National de Pathologie, Laboratoire National de Santé, Dudelange, Luxembourg.
使用人工智能的数字细胞学显示,与用于部病变的传统显微镜相适度一致. 人工智能系统发现了比传统方法更多的高度门病变.
科学领域:
- 细胞病理学 细胞病理学
- 数字病理学数字病理学
- 人工智能在医学中的应用
背景情况:
- 数字细胞学 (DC) 与人工智能 (AI) 在宫-阴道病变方面得到了验证.
- 这项研究评估DC/AI用于液基细胞学 (LBC) 标本.
研究的目的:
- 评估DC/AI的诊断性能与门LBC的常规显微镜 (CC) 相比.
- 为了确定DC/AI和CC在分类部病变中的一致性和一致性.
主要方法:
- 使用DC/AI系统审查了124张门LBC幻灯片.
- 使用2014年贝塞斯达系统,DC/AI的诊断与之前的CC诊断进行了比较.
主要成果:
- 通过这两种方法检测出相似数量的异常 (ASC-US+) 病例 (63 CC与62 DC/AI).
- 在CC和DC/AI之间观察到适度的协议 (κ=0.41).
- DC/AI发现的高度病变 (ASC-H,HSIL) 比CC更多.
结论:
- DC/AI 显示异常内LBC 病例的检测能力与CC.类似.
- 该DC/AI系统显示了提高检测高度状皮内皮病变的潜力.
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