Predicting Long COVID in the National COVID Cohort Collaborative Using Super Learner: Cohort Study
Predicting Long COVID in the National COVID Cohort Collaborative Using Super Learner: Cohort Study
Zachary Butzin-Dozier
1
, PhD ;
Yunwen Ji
1
, MA ;
Haodong Li
1
, MA ;
Jeremy Coyle
1
, PhD ;
Junming Shi
1
, MA ;
Rachael V Phillips
1
, PhD ;
Andrew N Mertens
1
, PhD ;
Romain Pirracchio
2
, MD ;
Mark J van der Laan
1
, PhD ;
Rena C Patel
3
, MD ;
John M Colford
1
, MD, PhD ;
Alan E Hubbard
1
, PhD ;
The National COVID Cohort Collaborative (N3C) Consortium
4
1
Division of Biostatistics, University of California Berkeley School of Public Health, Berkeley, CA, United States
2
Department of Anesthesia and Perioperative Care, University of California San Francisco, San Francisco, CA, United States
3
Department of Infectious Diseases, University of Alabama at Birmingham School of Medicine, Birmingham, AL, United States
4
Members are listed at the end of the manuscript, Rockville, MD, United States
Corresponding Author:
-
Zachary Butzin-Dozier, PhD
-
Division of Biostatistics
-
University of California Berkeley School of Public Health
-
2121 Berkeley Way
-
Berkeley, CA, 94720
-
United States
-
Phone:
1 3024376262
-
Email: zbutzin@berkeley.edu