Multi-scale data improves performance of machine learning model for long COVID identification.

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Title: Multi-scale data improves performance of machine learning model for long COVID identification.
Authors: Guardo C; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Xinmeng Z; Department of Computer Science, Vanderbilt University, Nashville, TN, USA., Gangireddy S; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Chao Y; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Kerchberger VE; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.; Division of Allergy, Pulmonary, and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA., Dickson AL; Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA., Pfaff ER; Department of Health Sciences, UNC Chapel Hill School of Medicine, Chapel Hill, NC, USA., Master H; Department of Health Sciences, UNC Chapel Hill School of Medicine, Chapel Hill, NC, USA.; Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA., Yi X; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.; Department of Computer Science, Vanderbilt University, Nashville, TN, USA., Basford M; Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA., Chute CG; Schools of Medicine, Public Health and Nursing, Johns Hopkins University, Baltimore, MD, USA., Tran NK; The PRIDE Study/PRIDEnet, Stanford University School of Medicine, Palo Alto, CA, USA., Mancuso S; The PRIDE Study/PRIDEnet, Stanford University School of Medicine, Palo Alto, CA, USA., Syed TA; Department of Health Data Science and Artificial Intelligence, UTHealth Houston, Houston, TX, USA., Zhongming Z; Department of Bioinformatics and Systems Medicine, UTHealth Houston, Houston, TX, USA., QiPing F; Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA., Haendel M; Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA., Lunt C; All of Us Research Program National Institutes of Health, Bethesda, MD, USA., Harris PA; All of Us Research Program National Institutes of Health, Bethesda, MD, USA., Lang L; Department of Biomedical Informatics, the Ohio State University, Columbus, OH, USA., Ginsburg GS; All of Us Research Program National Institutes of Health, Bethesda, MD, USA., Denny JC; All of Us Research Program National Institutes of Health, Bethesda, MD, USA., Roden DM; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Wei-Qi W; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA. wei-qi.wei@vumc.org.
Source: Communications medicine [Commun Med (Lond)] 2026 May 05; Vol. 6 (1). Date of Electronic Publication: 2026 May 05.
Publication Type: Journal Article
Journal Info: Publisher: Nature Portfolio Country of Publication: England NLM ID: 9918250414506676 Publication Model: Electronic Cited Medium: Internet ISSN: 2730-664X (Electronic) Linking ISSN: 2730664X NLM ISO Abbreviation: Commun Med (Lond) Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2730-664X
DOI:10.1038/s43856-026-01621-7