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Updated: Jun 7, 2025

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机器学习识别了基于免疫的生物标志物,这些生物标志物预测了在晚期肺癌中基于抗血管生成疗法的疗效

Peixin Chen1, Lei Cheng2, Chao Zhao2

  • 1Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China; School of Medicine, Tongji University, Shanghai 2000922, China.

International immunopharmacology
|November 18, 2024
PubMed
概括

整合治疗前循环的炎症生物标志物可以在接受抗血管性疗法的晚期肺癌患者中非侵入性预测临床结果. 这种基于免疫的模型预测了治疗反应和无进展生存率,有助于早期识别合适的候选人.

关键词:
抗血管性疗法是一种抗血管性疗法.肺癌是一种肺癌.机器学习 机器学习非侵入性的生物标志物.预报 预测 预测 预测瘤微环境 (TME) 是指瘤的微环境.

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