High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets

BACKGROUND: Converting electronic health record (EHR) entries to useful clinical inferences requires one to address the poor scalability of existing implementations of Generalized Linear Mixed Models (GLMM) for repeated measures. The major computational bottleneck concerns the numerical evaluation o...

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Detalhes bibliográficos
Publicado no:BMC Med Res Methodol
Main Authors: Bologa, Cristian G., Pankratz, Vernon Shane, Unruh, Mark L., Roumelioti, Maria Eleni, Shah, Vallabh, Shaffi, Saeed Kamran, Arzhan, Soraya, Cook, John, Argyropoulos, Christos
Formato: Artigo
Idioma:Inglês
Publicado em: BioMed Central 2021
Assuntos:
Technical Advance
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8310602/
https://ncbi.nlm.nih.gov/pubmed/34303362
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12874-021-01318-6
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