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Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19.
Subudhi, Sonu; Verma, Ashish; Patel, Ankit B; Hardin, C Corey; Khandekar, Melin J; Lee, Hang; McEvoy, Dustin; Stylianopoulos, Triantafyllos; Munn, Lance L; Dutta, Sayon; Jain, Rakesh K.
Afiliación
  • Subudhi S; Department of Medicine/Gastroenterology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Verma A; Department of Medicine/Renal Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Patel AB; Department of Medicine/Renal Division, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
  • Hardin CC; Department of Pulmonary and Critical Care Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Khandekar MJ; Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Lee H; Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • McEvoy D; Mass General Brigham Digital Health eCare, Somerville, MA, USA.
  • Stylianopoulos T; Cancer Biophysics Laboratory, Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus.
  • Munn LL; Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Dutta S; Mass General Brigham Digital Health eCare, Somerville, MA, USA. sdutta1@partners.org.
  • Jain RK; Department of Emergency Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. sdutta1@partners.org.
NPJ Digit Med ; 4(1): 87, 2021 May 21.
Article en En | MEDLINE | ID: mdl-34021235
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: NPJ Digit Med Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: NPJ Digit Med Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos