Known as SleepFM, the model was trained on nearly 600,000 hours of sleep data collected from 65,000 participants. The sleep data comes from polysomnography, a comprehensive sleep assessment that uses various sensors to record brain activity, heart activity, respiratory signals, leg movements, eye movements and more.

Polysomnography is the gold standard in sleep studies that monitor patients overnight in a lab. It is also, the researchers realized, an untapped gold mine of physiological data.

“We record an amazing number of signals when we study sleep,” said Emmanual Mignot, MD, Ph.D., the Craig Reynolds Professor in Sleep Medicine and co-senior author of the new study, which is published in Nature Medicine. “It’s a kind of general physiology that we study for eight hours in a subject who’s completely captive. It’s very data rich.”