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AI Listens to Sleep, Predicts Disease Risk
7 Jan
Summary
- AI model SleepFM predicts over 100 health conditions from sleep data.
- Sleep data analyzes brain, heart, and breathing patterns during rest.
- The AI achieved high accuracy, particularly for neurological and cardiac issues.
An innovative artificial intelligence model named SleepFM is now capable of predicting an individual's risk for more than 100 diseases using only their sleep data. This groundbreaking technology analyzes a vast array of physiological signals captured during sleep, offering a new window into future health challenges.
The AI was trained on nearly 600,000 hours of sleep data from thousands of individuals. Researchers found that SleepFM demonstrated remarkable accuracy in forecasting conditions ranging from various cancers and heart diseases to mental health disorders and overall mortality risk.
SleepFM's predictive power is particularly strong for conditions such as Parkinson's disease, dementia, and heart attack. The research team is actively working to refine the AI's algorithms and potentially integrate data from wearable devices to further improve its diagnostic capabilities.
