AI-based systems expand testing for diabetic retinopathy
Eye-exam technology is emerging as one of the first proven use cases of AI-based diagnostics in a clinical setting.
In a recent article on Fortune Well, retina specialist Aaron Lee, MD, C. Dan and Irene Hunter Endowed Professor in the UW Department of Ophthalmology and others discussed the value AI brings to ophthalmology, particularly the diagnosis and treatment of diabetic retinopathy.
Diabetic retinopathy results when high blood sugar harms blood vessels in the retina. While managing a patient’s diabetes can often prevent the disease — and there are treatments for more advanced stages — doctors say regular screenings are crucial for catching symptoms early.
The eye exams show that the AI’s ability to provide immediate results and the cost savings and convenience of not needing to make an extra appointment can have significant benefits for both patients and providers.
Dr. Lee called the approval of the first fully autonomous AI system in any field of medicine “a landmark moment in medical history,” following decades of research and a clinical trial involving 900 patients diagnosed with diabetes.
One potential downside of not having a doctor do the screening is that the algorithm solely looks for diabetic retinopathy, so it could miss other concerning diseases, like choroidal melanoma, Dr. Lee said. The algorithms generally “err on the side of caution” and over-refer patients.
The American Diabetes Association recommends that people with Type 2 diabetes get screened every one to two years, yet only about 60% of people living with diabetes get yearly eye exams.