Not just overnight sleep tests, Artificial intelligence (AI) too has the potential to improve efficiencies and precision in sleep medicine, resulting in a more patient-centered care and better outcomes, researchers have found.
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, according to a new position statement from the American Academy of Sleep Medicine.
“When we typically think of AI in sleep medicine, the obvious use case is for the scoring of sleep and associated events,” said 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 centres, AI and machine learning could advance sleep care, resulting in a more accurate diagnosis, prediction of disease and treatment prognosis.
“AI could allow us to derive more meaningful information from sleep studies, given that our current summary metrics, for example, the apnea-hypopnea index, aren’t predictive of the health and quality of life outcomes that are important to patients,” elaborated Goldstein.
AI Can Improve Diagnosis, Treatment Of Sleep Disorders
