Using AI to improve eye exams for diabetic patients

SCH: Harnessing Tensor Information to Improve EHR Data Quality for Accurate Data-driven Screening of Diabetic Retinopathy with Routine Lab Results

NIH-funded research Oklahoma State University Stillwater · NIH-10915517

This study is working on a smart tool that helps doctors figure out if their diabetic patients are at risk for eye problems, using regular lab results, so that more people can get the eye exams they need, especially those living in rural areas where eye care is hard to find.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionOklahoma State University Stillwater NIH-funded
Lab location1 site (Stillwater, United States)
Project IDNIH-10915517 on NIH RePORTER

What this research studies

This research aims to develop an artificial intelligence tool that helps primary care physicians assess the risk of diabetic retinopathy (DR) in patients using routine lab results and comorbidity data. By leveraging widely available health information, the tool seeks to increase the compliance rate of recommended eye exams among diabetic patients, particularly those in rural areas with limited access to ophthalmic care. The approach has shown promising preliminary results, achieving 90% accuracy in detecting DR without the need for specialized imaging equipment. This could significantly enhance early detection and intervention for patients at risk of vision loss.

Who could benefit from this research

Good fit: Ideal candidates for this research are diabetic patients, particularly those living in rural areas who may not have easy access to ophthalmic exams.

Not a fit: Patients who do not have diabetes or those who already have access to regular ophthalmic care may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to earlier detection of diabetic retinopathy, potentially preventing vision loss for thousands of patients.

How similar studies have performed: Preliminary studies have shown success in using similar AI approaches for detecting diabetic retinopathy, indicating a promising avenue for further research.

Where this research is happening

Stillwater, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-10 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.