AI Model Uses Sleep Data to Predict Long-Term Disease Risks
TL;DR Summary
The article introduces SleepFM, a large-scale foundation model trained on over 585,000 hours of sleep data from 65,000+ participants, which captures complex sleep physiology across multiple modalities and demonstrates strong predictive power for a wide range of diseases, outperforming traditional models and showing robust generalization across datasets and time.
Topics:top-news#deep-learning#disease-prediction#foundation-model#health-and-medicine#multimodal-psg#sleep-analysis
- A multimodal sleep foundation model for disease prediction Nature
- New AI model predicts disease risk while you sleep Stanford Medicine
- One Night of Sleep Data Can Predict Your Disease Risk Years Ahead ScienceBlog.com
- Scientists Decode Sleep Patterns to Forecast Your Future Health Risks Study Finds
- Stanford Medicine Develops AI Model to Predict Risk of Over 100 Health Conditions Using One Night’s Sleep Data geneonline.com
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