A deep-learning algorithm increased the accuracy of reading images for detecting retinal pathologies in patients with diabetes.
With the recent surge in artificial intelligence (AI) and machine learning, ophthalmology is already seeing the benefits.
“The push behind this has been to increase access to care for patients internationally in underserved areas that have limited resources and specialists,” said Ehsan Rahimy, MD.
That reach has also extended within the United States where patients with diabetes have relatively suboptimal adherence to screening guidelines for retinopathy, said Dr. Rahimy, vitreoretinal surgeon, Palo Alto Medical Foundation, Palo Alto, CA.
The first publication from the Google Brain team on the effectiveness of machine learning (Gulshan et al. JAMA 2016;316:2402-2410) found that a machine-learning algorithm performed as accurately as ophthalmologists in detecting referable diabetic retinopathy (DR), he noted.
These findings, and those of other related studies, are exciting but at the same time have opened a Pandora’s box of issues that need to be addressed, he noted.
Ehsan Rahimy, MD
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Dr. Rahimy is a physician consultant to Google.