Researchers Develop New AI Algorithm to Detect Diabetic Retinopathy

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SAN FRANCISCO—In a new study published online in Ophthalmology, the journal of the American Academy of Ophthalmology, researchers from Stanford University’s Byers Eye Institute describe how they used an artificial intelligence method known as deep-learning to create an automated algorithm to detect diabetic retinopathy.

"What we showed is that an artificial intelligence-based grading algorithm can be used to identify, with high reliability, which patients should be referred to an ophthalmologist for further evaluation and treatment," said Theodore Leng, MD, lead author. "If properly implemented on a worldwide basis, this algorithm has the potential to reduce the workload on doctors and increase the efficiency of limited healthcare resources. We hope that this technology will have the greatest impact in parts of the world where ophthalmologists are in short supply."

Another advantage is that the algorithm does not require any specialized, inaccessible, or costly computer equipment to grade images, according to the AAO. It can be run on a common personal computer or smartphone with average processors.

The Byers Eye Institute researchers joins a small but growing number of researchers worldwide who are using artificial intelligence to diagnose and perhaps even predict retinal disease. Last month at Vision Monday’s 2017 Global Leadership Summit in New York, research ophthalmologist Pearse Keane discussed in a video interview how he and his colleagues at Moorfields Eye Hospital in London are putting deep learning to work to detect macular degeneration as well as diabetic retinopathy.

Approval from the U.S. Food and Drug Administration is required before the algorithm can be used in patients on a broad basis. Dr. Leng and his team expect to conduct pilot trials in the near future, the AAO said.