Learning latent heterogeneity for type 2 diabetes patients using longitudinal health markers in electronic health records.

Lou, Jitong; Wang, Yuanjia; Li, Lang; Zeng, Donglin

Lou, Jitong; Wang, Yuanjia; Li, Lang; Zeng, Donglin.

Afiliación

Lou J; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Wang Y; Department of Biostatistics, Columbia University, New York City, New York, USA.
Li L; Department of Biomedical Informatics, Ohio State University, Columbus, Ohio, USA.
Zeng D; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Stat Med ; 40(8): 1930-1946, 2021 04 15.

Article en En | MEDLINE | ID: mdl-33586187

Asunto(s)

Diabetes Mellitus Tipo 2; Registros Electrónicos de Salud; Estudios de Cohortes; Hemoglobina Glucada/análisis; Humanos; Estudios Retrospectivos

Palabras clave

electronic health records; generalized linear models; kernel smoothing; latent process; type 2 diabetes

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diabetes Mellitus Tipo 2 / Registros Electrónicos de Salud Tipo de estudio: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Stat Med Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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