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Updated: Jan 29, 2026

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
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综合的多原子剖析揭示了通过机器学习优化清细胞脏细胞癌的巨驱动的预后特征

Wei Cao1, Wenyuan Zhuang1, Kai Xu1

  • 1Department of Urology, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, China.

Frontiers in immunology
|January 28, 2026
PubMed
概括

这项研究确定了清细胞细胞癌 (KIRC) 中五种不同的巨细胞子集,揭示了新的预后特征. 这种基于巨细胞异质性的特征,为改进KIRC诊断和治疗策略提供了潜力.

关键词:
清细胞细胞癌 (KIRC)高维权基因共同表达网络分析 (hdWGCNA)机器学习是机器学习.预后生物标志物 预后生物标志物单细胞RNA测序 (scRNA-seq) 是一种瘤微环境 (TME) 是指瘤的微环境.与瘤相关的巨细胞 (TAMs)

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