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The Stanford Medicine data science ecosystem for clinical and translational research.
Callahan, Alison; Ashley, Euan; Datta, Somalee; Desai, Priyamvada; Ferris, Todd A; Fries, Jason A; Halaas, Michael; Langlotz, Curtis P; Mackey, Sean; Posada, José D; Pfeffer, Michael A; Shah, Nigam H.
Afiliação
  • Callahan A; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA.
  • Ashley E; Department of Medicine, School of Medicine, Stanford University, Stanford, California, USA.
  • Datta S; Department of Genetics, School of Medicine, Stanford University, Stanford, California, USA.
  • Desai P; Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA.
  • Ferris TA; Technology and Digital Solutions, Stanford Medicine, Stanford University, Stanford, California, USA.
  • Fries JA; Technology and Digital Solutions, Stanford Medicine, Stanford University, Stanford, California, USA.
  • Halaas M; Technology and Digital Solutions, Stanford Medicine, Stanford University, Stanford, California, USA.
  • Langlotz CP; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA.
  • Mackey S; Technology and Digital Solutions, Stanford Medicine, Stanford University, Stanford, California, USA.
  • Posada JD; Department of Radiology, School of Medicine, Stanford University, Stanford, California, USA.
  • Pfeffer MA; Department of Anesthesia, School of Medicine, Stanford University, Stanford, California, USA.
  • Shah NH; Technology and Digital Solutions, Stanford Medicine, Stanford University, Stanford, California, USA.
JAMIA Open ; 6(3): ooad054, 2023 Oct.
Article em En | MEDLINE | ID: mdl-37545984
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Qualitative_research Idioma: En Revista: JAMIA Open Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Qualitative_research Idioma: En Revista: JAMIA Open Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos