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A machine learning approach for modeling decisions in the out of hospital cardiac arrest care workflow.
Harford, Samuel; Del Rios, Marina; Heinert, Sara; Weber, Joseph; Markul, Eddie; Tataris, Katie; Campbell, Teri; Vanden Hoek, Terry; Darabi, Houshang.
Afiliación
  • Harford S; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, USA.
  • Del Rios M; Department of Emergency Medicine, University of Iowa - Carver College of Medicine, Iowa City, IA, USA. marina-delrios@uiowa.edu.
  • Heinert S; Department of Emergency Medicine, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA.
  • Weber J; Department of Emergency Medicine, John H. Stroger, Jr. Hospital, Chicago, IL, USA.
  • Markul E; Illinois Masonic Medical Center, Chicago, IL, USA.
  • Tataris K; Department of Emergency Medicine, University of Chicago, Chicago, IL, USA.
  • Campbell T; Department of Emergency Medicine, University of Illinois at Chicago, Chicago, IL, USA.
  • Vanden Hoek T; Department of Emergency Medicine, University of Illinois at Chicago, Chicago, IL, USA.
  • Darabi H; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, USA.
BMC Med Inform Decis Mak ; 22(1): 21, 2022 01 25.
Article en En | MEDLINE | ID: mdl-35078470
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Servicios Médicos de Urgencia / Flujo de Trabajo / Paro Cardíaco Extrahospitalario Tipo de estudio: Etiology_studies / Guideline / Observational_studies / Prognostic_studies Límite: Adult / Humans Idioma: En Año: 2022 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Servicios Médicos de Urgencia / Flujo de Trabajo / Paro Cardíaco Extrahospitalario Tipo de estudio: Etiology_studies / Guideline / Observational_studies / Prognostic_studies Límite: Adult / Humans Idioma: En Año: 2022 Tipo del documento: Article