Multimodal cardiovascular risk profiling using self-supervised learning of polysomnography.

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Bibliographic Details
Title: Multimodal cardiovascular risk profiling using self-supervised learning of polysomnography.
Authors: He Z; Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States., Li H; Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States., Yuan G; School of Computing, University of Georgia, Athens, GA, United States., Killgore WDS; Department of Psychiatry, University of Arizona, Tucson, AZ, United States.; BIO5 Institute, University of Arizona, Tucson, AZ, United States., Quan SF; Department of Medicine, University of Arizona, Tucson, AZ, United States.; Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, United States., Chen CX; Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States.; BIO5 Institute, University of Arizona, Tucson, AZ, United States.; College of Nursing, University of Arizona, Tucson, AZ, United States., Li A; Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, United States.; BIO5 Institute, University of Arizona, Tucson, AZ, United States.
Source: Sleep [Sleep] 2026 Apr 16; Vol. 49 (4).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: United States NLM ID: 7809084 Publication Model: Print Cited Medium: Internet ISSN: 1550-9109 (Electronic) Linking ISSN: 01618105 NLM ISO Abbreviation: Sleep Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1550-9109
DOI:10.1093/sleep/zsaf371