Sleep Foundation Model Predicts Future Diseases From One Night of PSG Data

SleepFM: A 585,000-Hour Foundation Model That Turns One Night of Sleep Into a Disease Crystal Ball Can a single night of polysomnography (PSG) forecast dozens of future diseases without any expert labels? Yes. SleepFM self-trains on 65 000 unlabeled recordings and beats strong supervised baselines on 1 041 phenotypes, reaching 0.84 C-Index for all-cause mortality and 0.87 for dementia. What exact problem does SleepFM solve? Core question: “Why can’t current sleep-AI generalize to new hospitals or predict non-sleep diseases?” Traditional models need (i) costly manual labels, (ii) fixed electrode montages, and (iii) a fresh training run for every new task. …