Skip to main content

Sharing science to find answers

Find RECOVER Publications

Researchers within the RECOVER Initiative share their progress to understand, treat, and prevent Long COVID through research publications. Follow the latest science from RECOVER’s research studies below.

Visit the Research Summaries page to learn about RECOVER’s Long COVID research in a format that’s easy to understand.

Last updated:

105 Results

Filters

105 Results

Filters Applied:
EHR Pediatric

A machine learning-based phenotype for long COVID in children: An EHR-based study from the RECOVER program

Lorman, V; Razzaghi, H; Song, X; et. al., PLOS ONE,
Summary
EHR Adult New-onset and Pre-existing Conditions Risk Factors

De-black-boxing health AI: Demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository

Pfaff, ER; Girvin, AT; Crosskey, M; et al., Journal of American Medical Informatics Association,
Summary
Pathobiology

Lipopolysaccharide increases bitter taste sensitivity via epigenetic changes in Tas2r gene clusters

Lin, C; Jyotaki, M; Quinlan, J; et al., iScience,
Observational Adult

Researching COVID to enhance recovery (RECOVER) adult study protocol: Rationale, objectives, and design

Horwitz, LI; Thaweethai, T; Brosnahan, SB; et al., PLOS ONE,
Summary
Observational Adult Broad Symptoms Health Disparities New-onset and Pre-existing Conditions

Development of a definition of Postacute Sequelae of SARS-CoV-2 infection

Thaweethai, T; Jolley, SE; Karlson, EW; et al., JAMA,
Summary
Data Available
Q&A
EHR Adult Vaccination

Long COVID risk and pre-COVID vaccination in an EHR-based cohort study from the RECOVER Program

Brannock, MD; Chew, RF; Preiss, AJ; et al., Nature Communications,
Summary
Pathobiology Broad Symptoms

Anti-SARS-CoV-2 and autoantibody profiling of a COVID-19 patient with subacute psychosis who remitted after treatment with intravenous immunoglobulin

McAlpine, LS; Lifland, B; Check, JR; et al., Biological Psychiatry,
EHR Adult

Clinical encounter heterogeneity and methods for resolving in networked EHR data: A study from N3C and RECOVER programs

Leese, P; Anand, A; Girvin, A; et al., Journal of the American Medical Informatics Association,
Summary
Back to Top