Artificial intelligence improves diagnosis and risk prediction for vision-destroying disease

2022

Challenge

Age-related macular degeneration (AMD) is the leading cause of blindness in industrialized countries but often remains undiagnosed in the early stages when interventions would improve clinical outcomes. While early diagnosis of the disease is crucial, traditional diagnostic and assessment methods have limited accuracy, even when performed by specialists who are not available in many regions.

Advance

Using deep learning programs and large, long-term datasets, IRP researchers developed automated artificial intelligence (AI) algorithms to perform diagnosis, classification, and prognostic risk prediction for AMD. The algorithms were able to diagnose AMD and classify its severity using color photographs of the eye’s retina with greater accuracy than retina specialists. Moreover, other algorithms the researchers developed detected important features of the disease that would otherwise require advanced imaging techniques to identify. Finally, the IRP scientists' algorithms can use a patient’s data to predict his or her risk of progressing to advanced disease over the next decade — again, with greater accuracy than specialists.

Impact

AI techniques like deep learning are already beginning to transform clinical care for, and research on, diseases affecting the eye, such as diabetic retinopathy. This study shows that AI algorithms can be a boon to the study and treatment of AMD as well. Importantly, the development of AI algorithms that match or exceed specialist evaluations could enormously increase access to care. In addition, such algorithms can help patients receive a diagnosis more quickly, permitting early intervention that leads to improved clinical outcomes. To hasten their adoption in clinical and research settings, the IRP scientists have made their algorithms publicly available or embedded them in desktop software for research use.

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