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Updated: Jul 23, 2025

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用多变量纵向标记和临床终点的关节潜伏类模型描述复杂的疾病进展

Cécile Proust-Lima1,2, Tiphaine Saulnier1, Viviane Philipps1

  • 1Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, Bordeaux, France.

Statistics in medicine
|July 18, 2023
PubMed
概括

这项研究引入了一种新的统计模型,用于识别复杂的神经退行性疾病 (如多重系统缩 (MSA)) 中的不同患者子组. 该方法揭示了五种独特的MSA亚现象,改善了对疾病进展的理解和预后的预测.

关键词:
一个类成员的类成员身份.聚类集群是指聚类的聚类.异质性的异质性联合建模 联合建模多个系统缩.多变量纵向数据多变量纵向数据神经退行性疾病的神经退行性疾病

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