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<meta name="description" content="Researchers from UW Medicine have found that artificial intelligence-based screening algorithms to diagnose diabetic retinopathy do not perform as well as they claim." />
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AI algorithms detect diabetic eye disease inconsistently
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<span>AI algorithms detect diabetic eye disease inconsistently</span>
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Although some artificial intelligence software tested reasonably well, only one met the performance of human screeners, researchers found.
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January 5, 2021
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<a href="/about/news-and-events/news?topic=392" hreflang="en">Artificial Intelligence</a>
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<a href="/about/news-and-events/news?topic=13" hreflang="en">Diabetic Eye Disease</a>
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<a href="/about/news-and-events/news?topic=404" hreflang="en">Imaging</a>
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<p>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.</p><p>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).</p><p>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.</p>
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