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Updated: Jul 23, 2026

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
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通过单细胞景观分析在 LUAD 中构建代谢重编程生存风险框架:通过遗传算法优化进行三阶段合体学习

Xinti Sun1, Minyu Nong2, Fei Meng1

  • 1Department of Cardiothoracic Surgery, Tianjin Medical University General Hospital, Tianjin, China.

Journal of translational medicine
|April 15, 2024
PubMed
概括

这项研究引入了一种新的三阶段合体学习模型 (3S-MMR),通过分析代谢重编程来预测肺腺癌 (LUAD) 的预后. 3S-MMR得分提供了关于LUAD异质性和潜在的免疫治疗反应的见解.

关键词:
组合学习学习 组合学习遗传算法 遗传算法 遗传算法代谢重编程是一种代谢重编程.网络工具 网络工具

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