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机器学习模型用于个性化骨质放射性瘤风险预测在头部和部癌症.

Mohammad Moharrami1,2, Erin Watson1,2, Shao Hui Huang3

  • 1Faculty of Dentistry, University of Toronto, Toronto, ON, Canada.

Journal of medical systems
|March 9, 2026
PubMed
概括

这项研究开发了一种5个特征的随机生存森林模型,用于预测头部和部放射治疗 (RT) 后的骨质放射性缩 (ORN) 风险,并准确地考虑死亡等竞争风险.

关键词:
竞争的风险 竞争的风险微灰色回归的微灰色回归方法头癌是头部和部的癌症.骨质放射性脑缩的发生预测建模的预测建模.随机生存森林是随机生存的森林.

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