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AI algorithms detect diabetic eye disease inconsistently

Although some artificial intelligence software tested reasonably well, only one met the performance of human screeners, researchers found.
January 5, 2021
Artificial Intelligence Diabetic Eye Disease Imaging
Clinical Research
Grantee

Diabetes continues to be the leading cause of new cases of blindness among adults in the United States. But the current shortage of eye-care providers would make it impossible to keep up with demand to provide the requisite annual screenings for this population. A new study looks at the effectiveness of seven artificial intelligence-based screening algorithms to diagnose diabetic retinopathy, the most common diabetic eye disease leading to vision loss.

In a paper published Jan. 5 in Diabetes Care, researchers compared the algorithms against the diagnostic expertise of retina specialists. Five companies produced the tested algorithms – two in the United States (Eyenuk, Retina-AI Health), one in China (Airdoc), one in Portugal (Retmarker), and one in France (OphtAI).

The researchers found that the algorithms don’t perform as well as they claim. Many of these companies are reporting excellent results in clinical studies. But their performance in a real-world setting was unknown.