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English(EN) Distinguishing case-mix from context heterogeneity in prognostic regression model synthesis settings

新方法区分预后模型中的病例组合与背景异质性

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新方法，用于区分预后回归模型中的病例组合与背景异质性，特别是在综合来自多个站点的数据时。该方法包括在降维空间中拟合特定站点的局部回归，将平滑系数曲面划分为跨站点参考和特定站点的偏差。这种诊断区分有助于确定是应使用联合回归模型还是特定站点回归模型进行分析，这一点已在慢性阻塞性肺病试验中得到证明。 AI

排序理由 该集群包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

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新方法区分预后模型中的病例组合与背景异质性

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该集群包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Max Behrens, Janis M. Nolde, Eleni Papakonstantinou, Gabriele Bellerino, Theodoros Evrenoglou, Angelika Rohde, Daiana Stolz, Moritz Hess, Harald Binder ·

    在预后回归模型综合设置中区分病例组合与背景异质性

    arXiv:2608.12885v1 Announce Type: cross Abstract: Prognostic regression models often synthesize data from multiple sites, whether within a multi-site study, across federated settings, or in individual participant data meta-analysis. Here, a site is any data source, such as a hosp…

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