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Updated: Jul 19, 2025

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带有混合效应的轨迹集群分类模型:考虑到分类不确定性的推理

Charlotte Dugourd1,2,3,4, Amna Abichou-Klich1,2,3,4, René Ecochard1,2,3,4

  • 1Service de Biostatistique, Hospices Civils de Lyon, Lyon, France.

Statistics in medicine
|August 15, 2023
PubMed
概括

本研究引入了一个随机EM算法 (SEM),通过考虑不确定性来改善患者生物标志物轨迹分类. 对于了解患者子组和治疗效应,SEM提供了更准确的置信区间.

关键词:
在 SEM-CEM 算法中.这是分类分类的分类.在信任间隔的信任间隔.纵向数据 纵向数据 纵向数据混合效应模型的混合效应模型.

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Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
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