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Early results suggest participant diversity and novel measures will enable new, artificial intelligence-driven insights.
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November 8, 2024
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<p>Researchers today are releasing the flagship dataset from an ambitious study of biomarkers and environmental factors that might influence the development of type 2 diabetes, which is associated with a range of eye diseases such as diabetic retinopathy. Because the study participants include people with no diabetes and others with various stages of the condition, the early findings hint at a tapestry of information distinct from previous research.</p><p>For instance, data from a customized environmental sensor in participants’ homes show a clear association between disease state and exposure to tiny particulates of pollution. The collected data also includes survey responses, depression scales, eye-imaging scans and traditional measures of glucose and other biologic variables.</p><p>All of these data are intended to be mined by artificial intelligence for novel insights about risks, preventive measures, and pathways between disease and health.</p><p>“We see data supporting heterogeneity among type 2 diabetes patients — that people aren’t all dealing with the same thing. And because we’re getting such large, granular datasets, researchers will be able to explore this deeply,” said Dr. <a href="https://www.uwmedicine.org/bios/cecilia-lee#about-tab">Cecilia Lee</a>, a professor of ophthalmology at the University of Washington School of Medicine.</p><p>The project is funded through a grant from Bridge2AI, an NIH Common Fund Program, supported by the National Eye Institute.</p><p>To learn more, <a href="https://newsroom.uw.edu/news-releases/flagship-ai-ready-dataset-released-in-type-2-diabetes-study">read the news from the University of Washington newsroom</a>.</p>
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