Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes

Reese, J. T., Blau, H., Casiraghi, E., Bergquist, T., Loomba, J. J., Callahan, T. J., Laraway, B., Antonescu, C., Coleman, B., Gargano, M., Wilkins, K. J., Cappelletti, L., Fontana, T., Ammar, N., Antony, B., Murali, T. M., Caufield, J. H., Karlebach, G., McMurry, J. A., … Divers, J. (2023). Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes. EBioMedicine, 87, 104413. https://doi.org/10.1016/j.ebiom.2022.104413
Authors:
Justin Reese
Hannah Blau
Elena Casiraghi
Timothy Bergquist
Johanna Loomba
PheKnowLator Ecosystem Developers
Bryan Laraway
Corneliu Antonescu
Ben Coleman
Michael Gargano
Kenneth J. Wilkins
Luca Cappelletti
Tommaso Fontana
Nariman Ammar
Blessy Antony
T. M. Murali
J. Harry Caufield
Guy Karlebach
Julie A. McMurry
Andrew E. Williams
Richard A. Moffitt
Jineta Banerjee
Anthony Solomonides
Hannah Davis
Kristin Kostka
Giorgio Valentini
David Sahner
Christopher G. Chute
Charisse Madlock‐Brown
Melissa Haendel
Peter N. Robinson
Heidi Spratt
Shyam Visweswaran
Joseph Eugene Flack
Yun Jae Yoo
Davera Gabriel
G. Caleb Alexander
Hemalkumar B. Mehta
Feifan Liu
Robert Miller
Rachel Wong
Elaine Hill
Lorna E. Thorpe
Jasmin Divers
Affiliated Authors:
PheKnowLator Ecosystem Developers
Columbia Affiliation:
Subjects:
COVID-19 (MeSH)
Post-Acute COVID-19 Syndrome (MeSH)
Neurological Manifestations of COVID-19 Infection (OpenAlex Topic)
Coronavirus Disease 2019 (OpenAlex Topic)
Role of Microglia in Neurological Disorders (OpenAlex Topic)
Author Keywords:
covid-19
human phenotype ontology
long covid
machine learning
precision medicine
semantic similarity
elink
Publication Type:
Article
Unique ID:
10.1016/j.ebiom.2022.104413
PMID:
36563487
DOI:
10.1016/j.ebiom.2022.104413
Journal:
EBioMedicine
Publication Date:
Data Source:
OpenAlex
Source Link:
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Record Created: