Predicting diabetes clinical outcomes using longitudinal risk factor trajectories.

Simon, Gyorgy J; Peterson, Kevin A; Castro, M Regina; Steinbach, Michael S; Kumar, Vipin; Caraballo, Pedro J

Simon, Gyorgy J; Peterson, Kevin A; Castro, M Regina; Steinbach, Michael S; Kumar, Vipin; Caraballo, Pedro J.

Afiliación

Simon GJ; Department of Medicine, University of Minnesota, Minneapolis, USA. simo0342@umn.edu.
Peterson KA; Institute for Health Informatics, University of Minnesota, Minneapolis, USA. simo0342@umn.edu.
Castro MR; Department of Family Medicine, University of Minnesota, Minneapolis, USA.
Steinbach MS; Division of Endocrinology, Mayo Clinic, Rochester, USA.
Kumar V; Department of Computer Science and Engineering, University of Minnesota, Minneapolis, USA.
Caraballo PJ; Department of Computer Science and Engineering, University of Minnesota, Minneapolis, USA.

BMC Med Inform Decis Mak ; 20(1): 6, 2020 01 08.

Article en En | MEDLINE | ID: mdl-31914992

Asunto(s)

Diabetes Mellitus Tipo 2/diagnóstico; Diabetes Mellitus Tipo 2/prevención & control; Adulto; Glucemia; Femenino; Humanos; Masculino; Persona de Mediana Edad; Pronóstico; Modelos de Riesgos Proporcionales; Estudios Retrospectivos; Factores de Riesgo

Palabras clave

Diabetes; Diabetes trajectories; Prediabetes; Risk assessment

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diabetes Mellitus Tipo 2 Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

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