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  • [\'Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy. Thomas.Langer@unimib.it.\', \'Department of Anaesthesia and Intensive Care Medicine, Niguarda Ca\' Granda, Milan, Italy. Thomas.Langer@unimib.it.\', \'Department of Medicine and Surgery, University of Milan-Bicocca, Monza, Italy.\', \'Department of Anaesthesia and Intensive Care Medicine, Niguarda Ca\' Granda, Milan, Italy.\', \'Department of General oncologic and mini-invasive Surgery, Niguarda Ca\'Granda, Milan, Italy.\', \'Department of Emergency Medicine, Niguarda Ca\' Granda, Milan, Italy.\', \'Medical Department, Niguarda Ca\' Granda, Milan, Italy.\', \'Department of Laboratory Medicine, ASST Niguarda Hospital, University of Milan, Milan, Italy.\', \'Semeion Research Center of Sciences of Communication, Rome, Italy.\', \'Department of Mathematical and Statistical Sciences, University of Colorado at Denver, Denver, CO, USA.\', \'Centro Diagnostico Italiano, Milan, Italy.\', \'Villa Santa Maria Foundation, Tavernerio, Italy.\']
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  • -1
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  • 10.1186/s13049-020-00808-8
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  • Scandinavian journal of trauma, resuscitation and emergency medicine
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  • 33261629
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is ?:relation_isRelatedTo_publication of
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  • Development of machine learning models to predict RT-PCR results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with influenza-like symptoms using only basic clinical data.
?:type
?:year
  • 2020

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