Published online as an accepted paper in the Journal of Clinical Sleep Medicine, the position statement was developed by the AASM's Artificial Intelligence in Sleep Medicine Committee. According to the statement, the electrophysiological data collected during polysomnography -- the most comprehensive type of sleep study -- is well-positioned for enhanced analysis through AI and machine-assisted learning. "When we typically think of AI in sleep medicine, the obvious use case is for the scoring of sleep and associated events," said lead author and committee Chair Dr. Cathy Goldstein, associate professor of sleep medicine and neurology at the University of Michigan. "This would streamline the processes of sleep laboratories and free up sleep technologist time for direct patient care." Because of the vast amounts of data collected by sleep centers, AI and machine learning could advance sleep care, resulting in more accurate diagnoses, prediction of disease and treatment prognosis, characterization of disease subtypes, precision in sleep scoring, and optimization and personalization of sleep treatments.

Artificial intelligence has the potential to improve efficiencies and precision in sleep medicine, resulting in more patient-centered care and better outcomes, according to a new position statement from the American Academy of Sleep Medicine. Published online as an accepted paper in the Journal of Clinical Sleep Medicine, the position statement was developed by the AASM's Artificial Intelligence in Sleep Medicine Committee. According to the statement, the electrophysiological data collected during polysomnography--the most comprehensive type of sleep study--is well-positioned for enhanced analysis through AI and machine-assisted learning. "When we typically think of AI in sleep medicine, the obvious use case is for the scoring of sleep and associated events," said lead author and committee Chair Dr. Cathy Goldstein, associate professor of sleep medicine and neurology at the University of Michigan. "This would streamline the processes of sleep laboratories and free up sleep technologist time for direct patient care."