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对于第二次初级NSCLC患者的时间依赖可解释的生存预测模型.

Qiong Luo1, Qianyuan Zhang2, Haiyu Liu3

  • 1Department of Oncology Medicine, Fujian Medical University Union Hospital, Fuzhou, 350001, PR China.

International journal of medical informatics
|December 25, 2024
PubMed
概括

这项研究开发了一种准确的Blackboost生存模型,用于预测第二次原发性非小细胞肺癌 (SP-NSCLC) 患者的结果. 该模型利用机器学习确定了手术和阶段等关键预测因素,以改善个性化的生存预测.

关键词:
机器学习 机器学习总体生存预测总体生存预测第二种主要的非小细胞肺癌.外科手术 手术手术时间依赖的解释性

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