A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms.

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Title: A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms.
Authors: Epsi NJ; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America., Powers JH; Clinical Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States of America., Lindholm DA; Molecular Biology Laboratory, Brooke Army Medical Center, San Antonio, Texas, United States of America.; Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Mende K; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.; Molecular Biology Laboratory, Brooke Army Medical Center, San Antonio, Texas, United States of America., Malloy A; Department of Pediatrics, Walter Reed National Military Medical Center, Bethesda, Maryland, United States of America., Ganesan A; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.; Infectious Disease Clinic, Walter Reed National Military Medical Center, Bethesda, Maryland, United States of America., Huprikar N; Infectious Disease Clinic, Walter Reed National Military Medical Center, Bethesda, Maryland, United States of America., Lalani T; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.; Infectious Disease Clinical Research Program, Naval Medical Center Portsmouth, Portsmouth, Virginia, United States of America., Smith A; Infectious Disease Clinical Research Program, Naval Medical Center Portsmouth, Portsmouth, Virginia, United States of America., Mody RM; Infectious Disease Clinic, William Beaumont Army Medical Center, El Paso, Texas, United States of America., Jones MU; Pediatric Infectious Diseases, Tripler Army Medical Center, Honolulu, Hawaii, United States of America., Bazan SE; Family Nurse Practitioner and Women's Health Nurse Practitioner Program, Carl R. Darnall Army Medical Center, Fort Hood, Texas, United States of America., Colombo RE; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.; Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Infectious Disease Clinic, Madigan Army Medical Center, Tacoma, Washington, United States of America., Colombo CJ; Infectious Disease Clinic, Madigan Army Medical Center, Tacoma, Washington, United States of America., Ewers EC; Internal Medicine, Fort Belvoir Community Hospital, Fort Belvoir, Virginia, United States of America., Larson DT; Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Internal Medicine, Fort Belvoir Community Hospital, Fort Belvoir, Virginia, United States of America.; Infectious Disease Clinic, Naval Medical Center San Diego, San Diego, California, United States of America., Berjohn CM; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Infectious Disease Clinic, Naval Medical Center San Diego, San Diego, California, United States of America., Maldonado CJ; Department of Research and Clinical Investigation, Womack Army Medical Center, Fort Bragg, North Carolina, United States of America., Blair PW; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.; Department of Pathology, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Chenoweth J; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America., Saunders DL; Translational Medicine Unit, Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Livezey J; Translational Medicine Unit, Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Maves RC; Infectious Diseases and Critical Care Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America., Sanchez Edwards M; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America., Rozman JS; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America., Simons MP; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Tribble DR; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Agan BK; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America., Burgess TH; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America., Pollett SD; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.
Corporate Authors: EPICC COVID-19 Cohort Study Group
Source: PloS one [PLoS One] 2023 Feb 09; Vol. 18 (2), pp. e0281272. Date of Electronic Publication: 2023 Feb 09 (Print Publication: 2023).
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, N.I.H., Extramural
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
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  Data: A machine learning approach identifies distinct early-symptom cluster phenotypes which correlate with hospitalization, failure to return to activities, and prolonged COVID-19 symptoms.
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