SleepFM AI predicts 130 diseases from one night’s sleep
Stanford researchers unveil SleepFM, a foundation AI trained on nearly 600,000 hours of sleep data and long-term health records to forecast risk for about 130 diseases (and all-cause mortality) using only a single night of sleep captured via polysomnography; the model outperforms existing predictors (C-index >0.8 in many cases) and could someday be paired with wearables for real-time health monitoring, though current data come from sleep-clinic populations and may not generalize.