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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Detalles Bibliográficos
Autores principales: Vavougios, George D., Stavrou, Vasileios T., Konstantatos, Christoforos, Sinigalias, Pavlos-Christoforos, Zarogiannis, Sotirios G., Kolomvatsos, Konstantinos, Stamoulis, George, Gourgoulianis, Konstantinos I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029400/
https://www.ncbi.nlm.nih.gov/pubmed/35457497
http://dx.doi.org/10.3390/ijerph19084630

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029400/
https://www.ncbi.nlm.nih.gov/pubmed/35457497
http://dx.doi.org/10.3390/ijerph19084630

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