Artificial intelligence in sleep medicine: An American Academy of Sleep Medicine position statement

Cathy A. Goldstein, Richard B. Berry, David T. Kent, David A. Kristo, Azizi A. Seixas, Susan Redline, M. Brandon Westover, Fariha Abbasi-Feinberg, R. Nisha Aurora, Kelly A. Carden, Douglas B. Kirsch, Raman K. Malhotra, Jennifer L. Martin, Eric J. Olson, Kannan Ramar, Carol L. Rosen, James A. Rowley, Anita V. Shelgikar

Research output: Contribution to journalReview articlepeer-review

18 Scopus citations

Abstract

Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during polysomnography (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level.

Original languageEnglish
Pages (from-to)605-607
Number of pages3
JournalJournal of Clinical Sleep Medicine
Volume16
Issue number4
DOIs
StatePublished - Apr 15 2020

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