COVID-19 Phenotypes and Comorbidity: A Data-Driven, Pattern Recognition Approach Using National Representative Data from the United States

The aim of our study was to determine COVID-19 syndromic phenotypes in a data-driven manner using the survey results based on survey results from Carnegie Mellon University’s Delphi Group. Monthly survey results (>1 million responders per month; 320,326 responders with a certain COVID-19 test sta...

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Detalhes bibliográficos
Main Authors: George D. Vavougios, Vasileios T. Stavrou, Christoforos Konstantatos, Pavlos-Christoforos Sinigalias, Sotirios G. Zarogiannis, Konstantinos Kolomvatsos, George Stamoulis, Konstantinos I. Gourgoulianis
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2022-04-01
Colecção:International Journal of Environmental Research and Public Health
Assuntos:
COVID-19
pattern recognition
phenotypes
epidemiology
comorbidity
big data
Acesso em linha:https://www.mdpi.com/1660-4601/19/8/4630
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