Detection of referable diabetic retinopathy using machine learning on routine clinical data

Background Early detection of referable diabetic retinopathy (RDR) is crucial to prevent vision loss. We developed and validated a machine learning (ML) model using clinical and laboratory variables to predict RDR without ophthalmic imaging. Methods We enrolled 562 adults with diabetes who underwent fundus examination at a single tertiary center from June 2015 to December 2023, retrospectively and prospectively. RDR was defined as moderate nonproliferative diabetic retinopathy or worse, or diabe