A Multimodal Sleep Foundation Model Developed with 500K Hours of Sleep Recordings for Disease Predictions.

ABSTRACT: Sleep is a fundamental biological process with profound implications for physical and mental health, yet our understanding of its complex patterns and their relationships to a broad spectrum of diseases remains limited. While polysomnography (PSG), the gold standard for sleep analysis, captures rich multimodal physiological data, analyzing these measurements has been challenging due to limited flexibility across recording environments, poor generalizability across cohorts, and difficulty in leveraging information from multiple signals simultaneously. To address this gap, we curated over 585,000 hours of high-quality sleep recordings from approximately 65,000 participants across multiple cohorts and developed SleepFM, a multimodal sleep foundation model trained with a novel contrastive lear

SUBMITTER: Thapa R 

PROVIDER: S-EPMC11838666 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature