Artificial Intelligence Can Improve Diagnosis and Treatment of Sleep Disorders

Not just overnight sleep tests, Artificial intelligence (AI) also has the potential to improve efficiencies and precision in sleep medicine, resulting in more patient-centred 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.