Your browser doesn't support javascript.
loading
Overcoming barriers to the adoption and implementation of predictive modeling and machine learning in clinical care: what can we learn from US academic medical centers?
Watson, Joshua; Hutyra, Carolyn A; Clancy, Shayna M; Chandiramani, Anisha; Bedoya, Armando; Ilangovan, Kumar; Nderitu, Nancy; Poon, Eric G.
Afiliación
  • Watson J; Department of Surgery, Duke University School of Medicine, Durham, North Carolina, USA.
  • Hutyra CA; Department of Orthopedic Surgery, Duke University School of Medicine, Durham, North Carolina, USA.
  • Clancy SM; Duke Cancer Institute, Duke University School of Medicine, Durham, North Carolina, USA.
  • Chandiramani A; Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Bedoya A; Duke Health Technology Solutions, Duke University Health System, Durham, North Carolina, USA.
  • Ilangovan K; Duke Health Technology Solutions, Duke University Health System, Durham, North Carolina, USA.
  • Nderitu N; Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
  • Poon EG; Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA.
JAMIA Open ; 3(2): 167-172, 2020 Jul.
Article en En | MEDLINE | ID: mdl-32734155
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: JAMIA Open Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: JAMIA Open Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos