Artificial intelligence enhances efficacy of sleep disorder treatment
Thousands of Danes suffer from a range of sleep disorders, including sleep apnea and narcolepsy. Researchers at the University of Copenhagen have collaborated with the Danish Center for Sleep Medicine to develop an artificial intelligence algorithm that can improve diagnoses, treatments, and our overall understanding of these disorders.
Sleep disorder examination begin with admittance to a sleep clinic. A person's night sleep is monitored using a variety of measuring instruments. The 7-8 hours of measurements from the patient's overnight sleep are then reviewed by a sleep disorder specialist.
The doctor manually divides these 7-8 hours of sleep into 30-second intervals, which must all be classified as REM (rapid eye movement) sleep, light sleep, deep sleep, and so on. It is a time-consuming task that the algorithm can complete in a matter of seconds.
This project has allowed us to demonstrate that these measurements can be made very safely using machine learning, which is extremely important. "Many more patients can be assessed and diagnosed effectively by saving many hours of work," explains Poul Jennum, professor of neurophysiology and Head of the Danish Center for Sleep Medicine.