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Development and validation of prediction models for gestational diabetes treatment modality using supervised machine learning: a population-based cohort study.
Liao, Lauren D; Ferrara, Assiamira; Greenberg, Mara B; Ngo, Amanda L; Feng, Juanran; Zhang, Zhenhua; Bradshaw, Patrick T; Hubbard, Alan E; Zhu, Yeyi.
Afiliación
  • Liao LD; Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.
  • Ferrara A; Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Greenberg MB; Department of Obstetrics and Gynecology, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Ngo AL; Regional Perinatal Service Center, Kaiser Permanente Northern California, Santa Clara, CA, USA.
  • Feng J; Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Zhang Z; Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA.
  • Bradshaw PT; Department of Civil and Environmental Engineering, Stanford University, Palo Alto, CA, USA.
  • Hubbard AE; Division of Epidemiology, School of Public Health, University of California, Berkeley, CA, USA.
  • Zhu Y; Division of Biostatistics, School of Public Health, University of California, Berkeley, CA, USA.
BMC Med ; 20(1): 307, 2022 09 15.
Article en En | MEDLINE | ID: mdl-36104698
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diabetes Gestacional Tipo de estudio: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy Idioma: En Revista: BMC Med Asunto de la revista: MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Diabetes Gestacional Tipo de estudio: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy Idioma: En Revista: BMC Med Asunto de la revista: MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos