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在年轻和老年患者中,急性髓性白血病风险分层通过转录基因机器学习模型

Raíssa Silva1, Cédric Riedel1, Maïlis Amico2

  • 1IRMB, Université de Montpellier, INSERM, Montpellier, 34000, France.

Scientific reports
|November 13, 2025
PubMed
概括

这项研究使用机器学习揭示了急性髓性白血病 (AML) 中与年龄相关的分子差异. 这些发现突出了不同的瘤形状和免疫细胞变异,这对于改善AML风险分层和治疗策略至关重要.

关键词:
在急性髓性白血病中.在ELN分类中,ELN的分类.机器学习 机器学习在RNA-seqqq.这就是K-MER.文字转录 字体转录 字体转录

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Common myeloid progenitors (CMPs) are oligopotent cells that can differentiate into granulocytes and macrophages. Granulocytes and macrophages are essential for protecting the body against bacterial, viral, or fungal infections. They migrate from the bone marrow into the circulating blood to reach specific tissue sites where they differentiate and help in immune surveillance. However, they survive only for a few days and must be continuously made available to the organism to maintain a robust...
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