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Paper Details

A machine learning-based phenotype for long COVID in children: an EHR-based study from the RECOVER program.
medRxiv
2
2022
COVID, Children, EHR, MIS, MIS-C, MIS-C variants, Multisystem Inflammatory Syndrome, PASC, Patient, SARS, SARS CoV, SARS CoV-2, SARS-CoV-2, children, patients, pediatric Post-Acute Sequelae of SARS CoV-2
Author NameAffiliation
Vitaly LormanApplied Clinical Research Center, Children's Hospital of Philadelphia
Hanieh RazzaghiApplied Clinical Research Center, Children's Hospital of Philadelphia
Xing SongUniversity of Missouri School of Medicine
Keith E MorseDivision of Pediatric Hospital Medicine, Stanford University School of Medicine
Levon UtidjianApplied Clinical Research Center, Children's Hospital of Philadelphia
Andrea J AllenApplied Clinical Research Center, Children's Hospital of Philadelphia
Suchitra RaoUniversity of Colorado School of Medicine and Children's Hospital of Colorado
Colin M RogersonIndiana University School of Medicine
Tellen D BennettUniversity of Colorado School of Medicine and Children's Hospital Colorado
Hiroki MorizonoCenter for Genetic Medicine Research, Children's National Hospital
Daniel Eckrich
Ravi JhaveriAnn & Robert H. Lurie Children's Hospital of Chicago
Yungui HuangThe Research Institute at Nationwide Children's Hospital
Daksha RanadeSeattle Children's Hospital
Nathan M PajorCincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine
Grace M LeeStanford University School of Medicine
Christopher B ForrestApplied Clinical Research Center, Children's Hospital of Philadelphia
Leonard Charles BaileyApplied Clinical Research Center, Children's Hospital of Philadelphia
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