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AI Ready and Exploratory Atlas for Diabetes Insights
Sponsor: University of Washington
Summary
The study will collect a cross-sectional dataset of 4000 people across the US from diverse racial/ethnic groups who are either 1) healthy, or 2) belong in one of the three stages of diabetes severity (pre-diabetes/diet controlled, oral medication and/or non-insulin-injectable medication controlled, or insulin dependent), forming a total of four groups of patients. Clinical data (social determinants of health surveys, continuous glucose monitoring data, biomarkers, genetic data, retinal imaging, cognitive testing, etc.) will be collected. The purpose of this project is data generation to allow future creation of artificial intelligence/machine learning (AI/ML) algorithms aimed at defining disease trajectories and underlying genetic links in different racial/ethnic cohorts. A smaller subgroup of participants will be invited to come for a follow-up visit in year 4 of the project (longitudinal arm of the study). Data will be placed in an open-source repository and samples will be sent to the study sample repository and used for future research.
Key Details
Gender
All
Age Range
40 Years - 85 Years
Study Type
OBSERVATIONAL
Enrollment
4000
Start Date
2023-07-19
Completion Date
2027-01-01
Last Updated
2025-04-06
Healthy Volunteers
No
Conditions
Locations (3)
University of Alabama, Birmingham
Birmingham, Alabama, United States
UC San Diego
San Diego, California, United States
University of Washington
Seattle, Washington, United States