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A model to identify individuals with a high probability of a SARS-CoV-2 infection.
Kowall, B; Nonnemacher, M; Brune, B; Brinkmann, M; Dudda, M; Böttcher, J; Schmidt, B; Standl, F; Stolpe, S; Dittmer, U; Jöckel, K H; Stang, A.
Afiliação
  • Kowall B; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany. Electronic address: bernd.kowall@uk-essen.de.
  • Nonnemacher M; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany.
  • Brune B; Medical Emergency Service of the City of Essen, Germany; Department for Trauma, Hand and Reconstructive Surgery, University Hospital of Essen, Germany.
  • Brinkmann M; Center for Clinical Trials, University Hospital Essen, Germany.
  • Dudda M; Medical Emergency Service of the City of Essen, Germany; Department for Trauma, Hand and Reconstructive Surgery, University Hospital of Essen, Germany.
  • Böttcher J; Public Health Office of the City of Essen, Germany.
  • Schmidt B; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany.
  • Standl F; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany.
  • Stolpe S; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany.
  • Dittmer U; Institute for Virology, University Hospital Essen, Germany.
  • Jöckel KH; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany.
  • Stang A; Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, Hufelandstraße 55, 45147 Essen, Germany; School of Public Health, Department of Epidemiology, Boston University, Boston, United States.
J Infect ; 82(3): e32-e34, 2021 03.
Article em En | MEDLINE | ID: mdl-33245942
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Infecções por Coronavirus / COVID-19 Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Infecções por Coronavirus / COVID-19 Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article