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Article

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

International journal of environmental research and public health - 12 Apr 2022

Vavougios George D, Stavrou Vasileios T, Konstantatos Christoforos, Sinigalias Pavlos-Christoforos, Zarogiannis Sotirios G, Kolomvatsos Konstantinos, Stamoulis George, Gourgoulianis Konstantinos I

Abstract excerpt

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 status and disease duration <30 days were included in this study) were used sequentially in identifying and validating...

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Identifiers

PMID: 35457497
DOI: 10.3390/ijerph19084630
PMCID: PMC9029400

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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