SleepFM is a multimodal artificial intelligence foundation model engineered to derive latent representations of human physiology directly from polysomnographic recordings. Trained on a curated dataset exceeding 585,000 hours of PSG recordings from approximately 65,000 individuals, SleepFM establishes a novel paradigm in computational medicine. By shifting away from narrow, single-task deep learning models toward scalable, self-supervised pretraining, the model extracts high-d
Lloyd Price
Aug 16
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