Artificial Intelligence Passes Macular Degeneration Test
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A new artificial intelligence system — iPredict.Health from iHealthScreen — can accurately screen patients for age-related macular degeneration (AMD), results from a prospective clinical trial suggest.

"If we are able to diagnose AMD by screening in any clinical setting, we could start treating early and reduce blindness," said Alauddin, who presented the study findings at the virtual Association for Research in Vision and Ophthalmology 2020 Annual Meeting.

For their study, Alauddin and her colleagues used a deep-learning system trained to simulate the neural networks of the human brain to recognize patterns. They previously tested the system with the AREDS dataset and determined that it could identify AMD with 95.3% accuracy and could classify disease stage with 86.0% accuracy, which is comparable to rates achieved by human retina specialists.

To see whether the system could identify the disease in a real-life population, the researchers used a fundus camera to image both eyes of 150 unselected nondilated patients older than 50 years at New York Eye and Ear. All had high-quality images available and none had a confounding condition, such as diabetic retinopathy, macular edema, and previous retinal surgery.

The iHealth system classified 66 patients — on the basis of the worst eye — as referable for AMD because of intermediate or late AMD and 84 as nonreferable because of normal macula or early AMD.

When the system results were compared with readings from two ophthalmologists, accuracy was 88.67%; sensitivity, indicating true positives, was 86.57%; and specificity, indicating true negatives, was 90.36%.

The researchers have also used the system to predict which patients will progress to late AMD, and whether the disease will take the wet or dry form in these patients. They plan to follow the patients and test the accuracy of these predictions.