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Updated: Jan 25, 2026

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning
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机器学习方法能够非常准确地识别风险代谢功能障碍相关的型肝炎

Masaya Sato1,2, Takuma Nakatsuka1, Tatsuya Minami1

  • 1Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Hepatology research : the official journal of the Japan Society of Hepatology
|January 23, 2026
PubMed
概括

一个新的机器学习模型使用常规临床数据准确地识别了具有风险的代谢功能障碍相关的脂肪肝炎 (MASH). 这种非侵入性方法为预测晚期肝病提供了成本效益高的替代性肝硬度测量方法.

关键词:
这是一个快速得分.在风险MASHMASH.肝硬度测量 肝硬度测量机器学习是机器学习.

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