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Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival.
Kosyakovsky, Leah B; Somerset, Emily; Rogers, Angela J; Sklar, Michael; Mayers, Jared R; Toma, Augustin; Szekely, Yishay; Soussi, Sabri; Wang, Bo; Fan, Chun-Po S; Baron, Rebecca M; Lawler, Patrick R.
Afiliación
  • Kosyakovsky LB; Peter Munk Cardiac Centre, University Health Network, Toronto, Canada.
  • Somerset E; Department of Medicine, University of Toronto, Toronto, Canada.
  • Rogers AJ; Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
  • Sklar M; Peter Munk Cardiac Centre, University Health Network, Toronto, Canada.
  • Mayers JR; Rogers Computational Program, Ted Rogers Centre for Heart Research, University of Toronto, Toronto, Canada.
  • Toma A; Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Szekely Y; Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada.
  • Soussi S; Department of Anesthesia, St. Michael's Hospital, Toronto, Canada.
  • Wang B; Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
  • Fan CS; Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Baron RM; Department of Medicine, University of Toronto, Toronto, Canada.
  • Lawler PR; Peter Munk Cardiac Centre, University Health Network, Toronto, Canada.
Intensive Care Med Exp ; 10(1): 24, 2022 Jun 17.
Article en En | MEDLINE | ID: mdl-35710638
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Intensive Care Med Exp Año: 2022 Tipo del documento: Article País de afiliación: Canadá
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Intensive Care Med Exp Año: 2022 Tipo del documento: Article País de afiliación: Canadá