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June 7, 2026Diabetes

As of November 2025, data from 2280 participants has been released, including 358,999 files (3.87 TB) of data standardized for AI/ML research.

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Population

Target 4000 persons ≥ 40 years of age balanced for 4 categories of T2DM: non-diabetic…

Design

Other

Authors

DMDAWN MATTHIESJOJulia OwenGMGERALD MCGWIN

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Overview

The AI-READI project provides a large, multimodal, AI-ready dataset of individuals with and without type 2 diabetes to support future machine learning discoveries.

Key Points

  • The aim is to create a high-quality multimodal dataset for studying type 2 diabetes mellitus.
  • Recruited 4000 persons aged ≥ 40 years with various categories of type 2 diabetes.
  • Data is collected from sites in Birmingham, San Diego, and Seattle.
  • Included blood derivatives and multiple health domains relevant to T2DM.
  • 2280 participants have data released optimized for AI/ML research.
  • Current data release contains 358,999 files, totaling 3.87 TB.
  • Final dataset release from ~4000 participants is expected by November 2026.

Structured PICO

P
Population
Target 4000 (currently 2280) persons ≥ 40 years of age balanced for 4 categories of T2DM: non-diabetic, prediabetes/lifestyle-controlled, controlled by oral-medications/non-insulin injectables and insulin-dependent.

The AI-READI project provides a large, multimodal, AI-ready dataset of individuals with and without type 2 diabetes to support future machine learning discoveries.

Cite This Study

MATTHIES et al. (2026) studied this question.

synapsesocial.com/papers/6a250b2d7def13d035e1b363https://doi.org/10.2337/db26-2301-p
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