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单独使用AICyte的能力作为一个独立的选器,用于使用50%负切割值对宫细胞学进行分类

Xianxu Zeng^1,2, David Starr³, Juan Li⁴

¹Department of Pathology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Cancer cytopathology

|August 19, 2024

概括

AICyte人工智能系统可以有效地选宫细胞学病例,通过高精度识别负面病例,潜在地减少工作量. 这种人工智能工具显示出作为检测子宫癌的独立查方法的前景.

科学领域:

病理学病理学病理学
人工智能的人工智能
医学诊断医学诊断医学诊断

背景情况:

在宫细胞学查中,AICyte已经显示出潜力.
之前的研究表明,50%的负切割值可以减少工作量.

研究的目的:

评估AICyte可以减少宫细胞学查中的工作负载的假设.
为了评估AICyte的性能,使用50%的负切割值.

主要方法:

使用了瑞的WSI-2400 (AICyte) 系统.
分析了来自中国四个医院系统 (2018-2023) 的163,848例宫细胞学病例.
在统计上,AICyte结果与原始诊断进行了比较.

主要成果:

98.80%的AICyte指定的负面病例被证实是负面的.
高度病变的灵敏度和负预测值分别为90.77%和98.80%.
低度病变的灵敏度和负预测值分别为98.92%和99.94%.

结论:

AICyte可以作为子宫癌的独立查工具.
使用AICyte的50%负切断值可以优化工作流程并减少工作负载.
AICyte是用于宫癌查的潜在辅助方法,特别是在资源有限的环境中.

关键词:

人工智能的人工智能是人工智能.自动化自动化自动化自动化宫部查宫部查宫部查细胞病理学细胞病理学

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