AI can predict disease risk years in advance using a single night’s sleep

The test can track body functions. REPRESENTATION PIC/ISTOCK

A bad night of sleep leads to grogginess the next day, but may also point to serious health issues years before they appear. Researchers at Stanford Medicine have developed a new artificial intelligence system that can analyse detailed body signals from a single night of sleep and estimate a person's risk of developing more than 100 different diseases.

The system, called SleepFM, was trained using nearly 600,000 hours of sleep recordings from about 65,000 people. These recordings came from polysomnography, an in-depth sleep test that uses sensors to track brain activity, heart rhythms, breathing patterns, eye movements, leg motion, and other physiological signals throughout the night.

Polysomnography is widely considered the most reliable method for studying sleep, typically conducted overnight in specialised laboratories. Beyond diagnosing sleep disorders, researchers realised these tests capture an extraordinary amount of information about how the body functions over several uninterrupted hours.

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