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Updated: Feb 10, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.6K

单细胞测序,转录组测序和机器学习的整合,用于构建和验证肝细胞癌中与激素乙化相关的预后风险模型

Yajie Qi1,2, Fulin Wang1,2, Wenchao Ren3

  • 1National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

Frontiers in immunology
|February 9, 2026
PubMed
概括

这项研究使用基因素乙化数据开发了一种11基因肝肝细胞癌 (LIHC) 风险模型. 该模型预测了预后,并将NEU1确定为LIHC的关键治疗标.

关键词:
LIHC LIHC 的意思是欧盟国家1基因素乙化 基因素乙化 基因素乙化免疫微观环境 免疫微环境机器学习是机器学习.

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