Patients Back AI Diabetic Retinopathy Screening With Physician Oversight
A study of 100 adults with diabetes found broad comfort with AI-based diabetic retinopathy screening, but most participants wanted physician oversight. The findings come as AI tools move further into community diabetes care.
Fully autonomous artificial intelligence-based diabetic retinopathy screening can broaden access to care and improve diabetic retinopathy screening among underserved populations, especially in resource-limited settings. In a study of adults with diabetes at an urban academic medical center, participants were generally comfortable with the use of AI as part of the eye examination, but most would trust AI more if it were supervised by a doctor and did not believe that AI-based DR screening could replace a doctor’s visit.
Adults with diabetes were recruited to undergo imaging with a handheld AI fundus camera and respond to a survey on awareness of AI in healthcare, trust in AI systems, perceived efficiency of AI, preferences for personal interaction, and overall receptivity of AI in diabetic retinopathy screening. A total of 100 participants were included, with a mean age of 60 years; 52% were female; 24% were Hispanic, 20% non-Hispanic Black, 31% non-Hispanic White, and 25% other.
Most participants were aware of AI (78%) and its use in healthcare (70%), but fewer were aware of its application to eye disease (46%). Most believed AI could improve accuracy and protect confidentiality, both at 77%, yet 83% preferred physician oversight and would trust AI more if it were supervised by a doctor. Overall, 76% were comfortable with AI as part of the eye exam and 92% were satisfied with AI-based screening.
Despite this, only 31% felt AI could replace a doctor visit and 94% believed doctors will always remain responsible for diagnosing, even if AI was evaluating the scans. The study concluded that implementation of autonomous AI-based diabetic retinopathy screening should address the mismatch between the intended use of fully autonomous AI screening and participants’ understanding of the role that would mean for physicians.
The study noted that diabetic retinopathy is a leading cause of blindness in working-age adults and that early detection with timely intervention is critical in preventing vision loss. Fully autonomous AI-based detection of diabetic retinopathy was approved by the Food and Drug Administration in the US in 2018 and has the potential to dramatically improve screening rates and decrease preventable blindness.
More broadly, AI-driven approaches to community diabetes care are beginning to bring decision support, earlier insights, and practical tools directly into primary care and community settings. AI-enabled tools can support screening, risk stratification, and self-management directly in community settings, provided they are implemented thoughtfully and equitably. The article noted that AI-enabled apps and platforms are increasingly being used to support daily decisions related to nutrition, physical activity, medication adherence, and glucose monitoring, while conversational AI tools can deliver personalized education in plain language.
The broader community-care discussion also said AI tools must be validated across diverse populations to avoid reinforcing existing disparities, and that transparency and ongoing evaluation are essential to ensure fair and effective screening support. Patients and clinicians need to understand how recommendations are generated and how data are used, while clear governance frameworks are needed to define responsibility when AI influences care decisions.