结合临床与超声影像多模态数据构建小于胎龄儿预测模型 [PDF]
目的探索结合妊娠早期和妊娠中期的临床数据与超声影像多模态数据对小于胎龄儿(SGA)的预测价值,构建和内部验证基于多种机器学习算法的SGA 预测模型。方法本研究回顾性纳入单胎妊娠孕妇1 307例,根据INTERGROWTH-21st胎儿生长标准诊断SGA并采集包括临床一般资料、生化检验数据及产前超声筛查数据的多模态数据。轻度梯度增强算法(XGBoost)用于计算变量重要性,七种机器学习算法用于预测模型的构建与内部验证,受试者工作特性曲线下面积(AUC)作为衡量预测效能的主要指标,结合10 ...
朱云晓, 陈心雨
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Li R, Li H, Yang Z, Zhang X.
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