Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI)

Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI)

Introduction Artificial Intelligence Ready and Equitable for Diabetes Insights (AI-READI) is a data collection project on type 2 diabetes mellitus (T2DM) to facilitate the widespread use of artificial intelligence and machine learning (AI/ML) approaches to study salutogenesis (transitioning from T2D...

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Main Authors: Gerald McGwin, Linda M Zangwill, Nicholas Evans, Shannon McWeeney, Cecilia S Lee, Bhavesh Patel, Jeffrey C Edberg, Cynthia Owsley, Aaron Lee, Cecilia Lee, Sally L Baxter, Michael Snyder, Samantha Hurst, Nicole Ehrhardt, Christopher Chute, Dawn S Matthies, Julia P Owen, Amir Bahmani, Sally Baxter, Edward Boyko, Aaron Cohen, Jorge Contreras, Garrison Cottrell, Virginia de Sa, Jeffrey Edberg, Irl Hirsch, Michelle Hribar, T.Y. Alvin Liu, Bonnie Maldenado, Sara Singer, Bradley Voytek, Joseph Yracheta, Linda Zangwill
Format: Article
Language:English
Published: BMJ Publishing Group 2025-02-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/15/2/e097449.full
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https://bmjopen.bmj.com/content/15/2/e097449.full

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