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Comparing risk factors in severe COVID-19 using machine learning and non-machine learning methods: analysis from 2 international randomized controlled trials.

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Title: Comparing risk factors in severe COVID-19 using machine learning and non-machine learning methods: analysis from 2 international randomized controlled trials.
Authors: Møller Jensen C; CHIP, Centre of Excellence for Health, Immunity, and Infections, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark., Zargari Marandi R; CHIP, Centre of Excellence for Health, Immunity, and Infections, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark., Moestrup KS; CHIP, Centre of Excellence for Health, Immunity, and Infections, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark., Mourad A; Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States.; Duke Clinical Research Institute, Durham, NC 27701, United States., Mena Lora AJ; University of Illinois Chicago, Chicago, IL 60607, United States., Sherman BT; Frederick National Laboratory for Cancer Research, Frederick, MD 21701, United States., Vock DM; Division of Biostatistics & Health Data Science, University of Minnesota, Minneapolis, MN 55414, United States., Nordwall JA; Division of Biostatistics & Health Data Science, University of Minnesota, Minneapolis, MN 55414, United States., Carson JM; Kirby Institute, University of New South Wales, Sydney, NSW 2052, Australia., Peiffer-Smadja N; Université Paris Cité et Université Sorbonne Paris Nord, Inserm, IAME, Paris, 75018, France.; Infectious and Tropical Diseases Department, Hopital Bichat - Claude Bernard, AP-HP, Paris, 75018, France., Aggarwal NR; Division of Pulmonary, Allergy, and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO 80045, United States., Naiman NE; Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States., Brown SM; Pulmonary/Critical Care Medicine, Intermountain Medical Center, Salt Lake City, UT 84132, United States., Barrett TW; VA Portland Health Care System, Portland, OR 97239, United States.; Oregon Health & Science University, Portland, OR 97239, United States., Hatlen T; Harbor-UCLA Medical Center, Torrance, CA 90502, United States., Kjærgaard VS; CHIP, Centre of Excellence for Health, Immunity, and Infections, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark., Chang W; Frederick National Laboratory for Cancer Research, Frederick, MD 21701, United States., Sydes MR; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, UCL, London WC1V 6LJ, United Kingdom.; Data for R&D, Transformation Directorate, NHS England, London, United Kingdom., Lundgren J; CHIP, Centre of Excellence for Health, Immunity, and Infections, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark.; Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark.; Department of Clinical Medicine, University of Copenhagen, Copenhagen N, 2200, Denmark., Jensen TO; CHIP, Centre of Excellence for Health, Immunity, and Infections, Rigshospitalet, University of Copenhagen, Copenhagen Ø, 2100, Denmark.
Corporate Authors: STRIVE Network and ITAC and TICO Study Groups
Source: JAMIA open [JAMIA Open] 2026 Jun 23; Vol. 9 (3), pp. ooag079. Date of Electronic Publication: 2026 Jun 23 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press on behalf of the American Medical Informatics Association Country of Publication: United States NLM ID: 101730643 Publication Model: eCollection Cited Medium: Internet ISSN: 2574-2531 (Electronic) Linking ISSN: 25742531 NLM ISO Abbreviation: JAMIA Open Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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ISSN:2574-2531
DOI:10.1093/jamiaopen/ooag079