Creating a comprehensive dataset to improve understanding of type 2 diabetes
Bridge2AI: Salutogenesis Data Generation Project
The AI-READI project is gathering information from over 4,000 people with type 2 diabetes to better understand the condition and improve treatment, and we want to include a diverse group of participants to make sure everyone's experience is represented.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project ID | NIH-10471118 on NIH RePORTER |
What this research studies
The AI-READI project aims to develop a large, ethically-sourced dataset that will enhance our understanding of type 2 diabetes mellitus (T2DM) and its pathways to health. By collecting data from over 4,000 participants across the United States, including diverse racial and ethnic groups, the research will focus on both cross-sectional and longitudinal data to analyze disease trajectories. This innovative approach will utilize advanced artificial intelligence and machine learning techniques to identify patterns and insights that can lead to better management and treatment of diabetes. Participants will contribute to a dataset that is designed to be inclusive and representative of various stages of diabetes.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with type 2 diabetes, particularly those from diverse racial and ethnic backgrounds.
Not a fit: Patients without a diagnosis of type 2 diabetes or those who do not meet the study's demographic criteria may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved strategies for managing and potentially reversing type 2 diabetes.
How similar studies have performed: Previous research utilizing large, multimodal datasets has shown promise in advancing our understanding of complex diseases, suggesting that this approach could yield valuable insights.
Where this research is happening
Seattle, United States
- University of Washington — Seattle, United States (Active)
Researchers
- Principal investigator: Lee, Aaron — University of Washington
- Study coordinator: Lee, Aaron
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.