ICT&health January 7, 2026
A poor night’s sleep often feels like a temporary inconvenience, but it can also be an early sign of health problems that only manifest themselves years later. Researchers at Stanford Medicine, together with international partners, have developed a new artificial intelligence model that can predict the risk of developing more than a hundred conditions based on physiological data from a single night’s sleep. The model, SleepFM, shows how sleep data can become a powerful building block for predictive and personalised medicine.
SleepFM has been trained on nearly 600,000 hours of polysomnography data from approximately 65,000 participants. Polysomnography is the gold standard in sleep research and records a wide range of physiological signals throughout the night, including brain activity, heart activity,...
Today's Sponsors
Today's Sponsor