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在儿科高剂量甲状腺素治疗中延迟分泌的风险因素识别:对现实世界的数据进行机器学习分析

Chengyu Zhou1,2, Yali Qian1, Yao Xue3

  • 1Pediatric Intensive Care Unit, Children's Hospital of Nanjing Medical University, Nanjing, China.

Frontiers in pharmacology
|October 3, 2025
PubMed
概括

在接受高剂量甲索特雷克萨 (HDMTX) 治疗的儿科患者中,延迟甲索特雷克萨的分泌是常见的. 使用临床数据的XGBoost模型准确预测延迟分泌,确定血清肌素是关键风险因素.

关键词:
延迟的排泄延迟的排泄机器学习是机器学习.甲基特雷克萨酸盐的使用方法儿科 儿科 儿科预测模型是一个预测模型.

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