New AI tool improves sleep analysis and disorder detection

Researchers at the Icahn School of Medicine have created a new AI tool called PFTSleep, which analyzes an entire night's sleep data. This tool uses advanced technology to improve sleep stage classification, moving beyond traditional methods that rely on short data segments. The AI model was trained on over one million hours of sleep data, allowing it to recognize patterns across different populations. This comprehensive approach aims to enhance sleep analysis and support the detection of sleep disorders and health risks. While the tool shows promise, it is designed to assist sleep specialists rather than replace them. Future research will focus on expanding its capabilities to identify sleep disorders and predict health outcomes more effectively.