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Machine learning automatically detects COVID-19 using chest CTs in a large multicenter cohort.
Mortani Barbosa, Eduardo J; Georgescu, Bogdan; Chaganti, Shikha; Aleman, Gorka Bastarrika; Cabrero, Jordi Broncano; Chabin, Guillaume; Flohr, Thomas; Grenier, Philippe; Grbic, Sasa; Gupta, Nakul; Mellot, François; Nicolaou, Savvas; Re, Thomas; Sanelli, Pina; Sauter, Alexander W; Yoo, Youngjin; Ziebandt, Valentin; Comaniciu, Dorin.
Afiliación
  • Mortani Barbosa EJ; Division of Cardiothoracic Imaging, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Ground Floor Founders Bldg, Philadelphia, PA, 19104, USA. Eduardo.Barbosa@pennmedicine.upenn.edu.
  • Georgescu B; Penn Medicine, Philadelphia, PA, USA. Eduardo.Barbosa@pennmedicine.upenn.edu.
  • Chaganti S; Siemens Healthineers, Princeton, NJ, USA.
  • Aleman GB; Siemens Healthineers, Princeton, NJ, USA.
  • Cabrero JB; Clínica Universidad de Navarra, Navarra, Spain.
  • Chabin G; Health Time, Jaén, Spain.
  • Flohr T; Siemens Healthineers, Paris, France.
  • Grenier P; Siemens Healthineers, Forchheim, Germany.
  • Grbic S; Hôpital Foch, Suresnes, France.
  • Gupta N; Siemens Healthineers, Princeton, NJ, USA.
  • Mellot F; Houston Methodist, Houston, TX, USA.
  • Nicolaou S; Hôpital Foch, Suresnes, France.
  • Re T; Vancouver General Hospital, Vancouver, BC, Canada.
  • Sanelli P; Siemens Healthineers, Princeton, NJ, USA.
  • Sauter AW; Donald and Barbara Zucker School of Medicine, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
  • Yoo Y; University Hospital Basel, Clinic of Radiology & Nuclear medicine, Basel, Switzerland.
  • Ziebandt V; Siemens Healthineers, Princeton, NJ, USA.
  • Comaniciu D; Siemens Healthineers, Forchheim, Germany.
Eur Radiol ; 31(11): 8775-8785, 2021 Nov.
Article en En | MEDLINE | ID: mdl-33934177
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA 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 Asunto principal: COVID-19 Tipo de estudio: Observational_studies Límite: Humans Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos