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Updated: Sep 17, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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机器学习揭示了缺氧-免疫基因枢纽,用于甲状腺相关眼科病的临床分层

Lu Chen1,2,3,4,5, Sha Wang1,2,3,4, Jinwei Wang1,2,3,4

  • 1Eye Center of Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China.

Scientific reports
|July 2, 2025
PubMed
概括

缺氧通过改变基因表达和促进轨道纤维细胞的变化,驱动甲状腺相关的眼病 (TAO). 这项研究确定了关键的基因和免疫细胞,为TAO诊断和干预提供了一个预测模型.

关键词:
氧气过低是因为缺氧.免疫微观环境 免疫微观环境预测模型是一个预测模型.甲状腺相关的眼睛疾病.

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