The Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) aims to create and share a multimodal dataset specifically optimized for artificial intelligence research in type 2 diabetes mellitus.

This innovative dataset is designed to facilitate research that addresses disparities and promotes equity in diabetes care and treatment.

AI-READI represents a multidisciplinary data-generation initiative, involving various institutions and researchers focused on enhancing data accessibility to improve diabetes research.

The consortium behind AI-READI includes a writing committee and numerous principal investigators from diverse fields, reflecting a collaborative effort to advance diabetes research.

Key collaborators in this project include prominent universities such as the University of California San Diego, Johns Hopkins University, and Stanford University, with significant contributions from the National Institutes of Health (NIH).

The project has received substantial support from the US National Institutes of Health, specifically through grants OT2OD032644 and P30 DK035816, along with cloud services from Microsoft AI for Good Lab.

Partnerships with several companies, including Topcon Corporation, Optomed, and Garmin, have provided devices and research discounts to support the study.

AI-READI emphasizes the importance of ethical considerations in AI data collection and sharing, ensuring that the dataset can be used responsibly and effectively.

Acknowledgment is given to study participants and the AI-READI Advisory Council for their invaluable contributions to the project.

The findings and methodologies of the AI-READI project have been published in the journal Nature Metabolism, marking a significant milestone in diabetes research.