Salutogenesis
The Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI)
The AI-READI team is building an ethically sourced, multi-institutional dataset on type 2 diabetes to advance AI/ML research and uncover pathways from disease to health. With data from more than 4,000 participants, plus longitudinal follow-up for a subset, the project aims to create a foundational resource that is free from existing classification biases. This dataset will support the reconstruction of a temporal atlas of T2DM progression and recovery, enabling new insights into prevention, management, and reversal.
Meet the team behind AI-READI, or learn more about the research driving it forward.
Who We Are
Aaron Lee
Contact Principal Investigator
Washington University St. Louis
Cecilia Lee
Washington University St. Louis
Sally Baxter
Other Principal Investigator
University of California San Diego
Christopher Chute
Other Principal Investigator
Johns Hopkins University
Megan Collins
Other Principal Investigator
Johns Hopkins University
Kadija Ferryman
Johns Hopkins University
Michelle Hribar
Other Principal Investigator
Oregon Health & Science University
Samantha Hurst
Other Principal Investigator
University of California San Diego
Hiroshi Ishikawa
Other Principal Investigator
Oregon Health & Science University
T. Y. Alvin Liu
Johns Hopkins University
Gerald McGwin
Other Principal Investigator
University of Alabama at Birmingham
Shannon McWeeney
Other Principal Investigator
Oregon Health & Science University
Camille Nebeker
Other Principal Investigator
University of California San Diego
Cynthia Owsley
Other Principal Investigator
University of Alabama at Birmingham