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Updated: Sep 12, 2025

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
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基于深度学习的两步联合模型实现了在血清性溢出中智能识别脱皮细胞

Yige Yin1, Xiaotao Li2, Dongsheng Li3

  • 1Department of Orthopaedic, 989th Hospital of PLA, Luoyang 471031, China; Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China.

Computational biology and chemistry
|August 10, 2025
PubMed
概括

这项研究引入了一个两步的深度学习框架,用于精确的细胞病理学诊断血清溢出. 人工智能模型增强了异常细胞的检测和正常细胞的分类,提高了诊断的一致性.

关键词:
分类模型的分类模型.细胞病理学 细胞病理学对象检测模型的模型.血清性溢出 血清性溢出 血清性溢出

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