AI-powered sleep analysis using the SleepFM foundation model. Analyze polysomnography data for sleep staging and disease risk prediction.
Get StartedUpload your polysomnography recording in EDF or HDF5 format
SleepFM model processes your data using advanced deep learning
Get detailed visualizations and insights from your sleep data
SleepFM is a multimodal sleep foundation model trained on over 585,000 hours of polysomnography recordings from approximately 65,000 participants. Published in Nature Medicine (2025), it represents a breakthrough in sleep analysis and disease prediction.
The model achieves exceptional performance with C-Index scores of 0.84 for all-cause mortality, 0.85 for dementia, and 0.81 for myocardial infarction, among 130+ conditions.
Privacy & Security
All data is encrypted and securely stored. Your sleep recordings are processed with the highest standards of data protection and privacy.
Master advanced workflows like batch processing, referral management, and report customization with our comprehensive video library.
Streamline your clinical workflow with secure patient data sharing and collaborative review
Upload polysomnography recordings individually or in batches for multiple patients
AI-powered sleep staging and disease risk assessment completed in minutes
Review detailed visualizations, compare historical studies, and generate insights
Generate time-limited secure links to share results with referring physicians or specialists
Process up to 50 patient studies simultaneously with queue management and progress tracking
Compare multiple studies over time to track disease progression and treatment efficacy
End-to-end encryption, secure storage, and time-limited sharing links for patient privacy
Generate comprehensive PDF reports with sleep architecture analysis and risk assessments
Create and share analysis templates for standardized protocols across your practice
Dr. Sarah Chen, Sleep Medicine Specialist, uses the platform to manage her sleep lab's workflow. She uploads overnight PSG studies for 15 patients each week using batch upload, reviews the AI-generated sleep staging and disease risk predictions, and generates secure sharing links for referring cardiologists and neurologists. The longitudinal comparison feature helps her track treatment outcomes for patients with sleep apnea, while the custom templates ensure consistent analysis protocols across her team.
Sign in to start using the SleepFM Inference Platform
Get Started Now