2025 PRESENTER PROFILES
Advancing Diabetic Retinopathy Care—Integrating Clinical Insights, AI, and Health Equity
Friday, June 20, at 5:30 p.m. CT
Room W181 A-C • McCormick Place Convention Center
Mitigating Adoption Bias in Medical Autonomous AI—Quantifying the Balance between Accuracy and Access
Roomasa Channa, MD
Associate Professor,
University of Wisconsin
What is your presentation about?
We compared the adoption of two different artificial intelligence (AI) systems for detecting diabetic retinopathy: a desktop fundus camera and a handheld retina camera. We compare the adoption and accuracy of the two systems and evaluate their effectiveness in identifying cases of diabetic retinopathy, i.e. population achieved sensitivity as opposed to sensitivity alone.
How do you hope your presentation will impact diabetes research or care?
Blindness from diabetes continues to be a leading cause of vision loss in the United States. AI systems can help decrease that burden by providing essential screening services in underserved communities with limited access to specialty care. We hope to share the adoption and accuracy of two different AI systems at detecting diabetic retinopathy.
How did you become involved with this area of diabetes research or care?
As a retina surgeon, I often see the worst cases of diabetes-related eye disease in my clinic. Sometimes these cases are past the point of being treated. Every time I have to see a patient go blind from diabetes, I am reminded of how we could have prevented this devastating complication, if only we had diagnosed this earlier in the course of disease. It is this thought that keeps me going in my work in this area.
