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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Bibliografische gegevens
Hoofdauteurs: George D. Vavougios, Vasileios T. Stavrou, Christoforos Konstantatos, Pavlos-Christoforos Sinigalias, Sotirios G. Zarogiannis, Konstantinos Kolomvatsos, George Stamoulis, Konstantinos I. Gourgoulianis
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2022-04-01
Reeks:International Journal of Environmental Research and Public Health
Onderwerpen:
COVID-19
pattern recognition
phenotypes
epidemiology
comorbidity
big data
Online toegang:https://www.mdpi.com/1660-4601/19/8/4630
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