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  • [\'Department of Emergency, The First Medical Center to Chinese People\'s Liberation Army General Hospital, Beijing, China.\', \'Washington University in St. Louis, St. Louis, USA.\', \'School of Economics and Management, Beijing Jiaotong University, Beijing, China.\', \'Department of Emergency, Affiliated Hospital of Zunyi Medical University, Zunyi, China.\', \'School of Management, Beijing Union University, Beijing, China.\', \'School of E-Business and Logistics, Beijing Technology and Business University, Beijing, China.\', \'Department of Emergency, The Third Medical Center to Chinese People\'s Liberation Army General Hospital, Beijing, China. drchenwei@vip.sina.com.\', \'School of Economics and Management, Beijing Jiaotong University, Beijing, China. jingli@bjtu.edu.cn.\', \'Department of Emergency, The First Medical Center to Chinese People\'s Liberation Army General Hospital, Beijing, China. kunlunhe@plagh.org.\']
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  • 10.1038/s41598-021-02370-4
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  • Scientific reports
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  • 34848736
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  • 1.533
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  • An interpretable machine learning model based on a quick pre-screening system enables accurate deterioration risk prediction for COVID-19.
?:type
?:year
  • 2021

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