Predicting Diabetic Retinopathy

Vision loss from diabetic retinopathy brings substantial personal, health, and financial costs. The condition poses unique challenges in medically underserved communities, where patients may have trouble meeting the American Diabetes Association’s guidelines on annual eye examinations. Additionally, patients may be unaware that they have latent retinopathy because they are not yet experiencing any symptoms. Therefore, it is important to develop methods to assist clinicians in caring for diabetic patients.

Dr. Lola Ogunyemi’s team has performed research that demonstrates the potential of certain machine learning methods for identifying otherwise-underserved patients at high risk of diabetic retinopathy. These methods use clinical data collected during the patients’ care. Refinement of the methods to improve their sensitivity and specificity will be an important next step. This work was funded by the National Library of Medicine under grant 1 R01 LM012309.

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