New machine learning tools to understand sleep data in adults with diabetes

Who could benefit from this research

What this research studies

This project creates advanced machine learning techniques to extract meaningful patterns from continuous glucose monitoring and ambulatory blood pressure data collected from adults with type 2 diabetes and obstructive sleep apnea. By focusing on temporal features and precision phenotyping, the team aims to uncover how PAP therapy affects glucose control and blood pressure beyond simple averages. The study builds on data from a prior trial and emphasizes translating complex wearable data into actionable insights for better personal care. If successful, these methods could enable personalized treatment decisions and clearer understanding of who benefits most from PAP therapy.

Why it matters

Where this research is happening

• University of Michigan at Ann Arbor
  Ann Arbor, United States Active

Researchers

• Principal investigator: Gaynanova, Irina — University of Michigan at Ann Arbor
• Study coordinator: Gaynanova, Irina

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About this research

1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
3. For full project details, budget, and progress reports, visit the official NIH RePORTER page.