Detecting diabetic retinopathy through machine learning on electronic health record data from an urban, safety net healthcare system.
Clinical guidelines recommend annual eye examinations to detect diabetic retinopathy (DR) in patients with diabetes. However, timely DR detection remains a problem in medically underserved and under-resourced settings in the United States. Machine learning that identifies patients with latent/undiagnosed DR could help to address this problem.
Author(s): Ogunyemi, Omolola I, Gandhi, Meghal, Lee, Martin, Teklehaimanot, Senait, Daskivich, Lauren Patty, Hindman, David, Lopez, Kevin, Taira, Ricky K
DOI: 10.1093/jamiaopen/ooab066