Prediction of complications of diabetes mellitus utilising novel retinal image analysis, genetics, and linked electronic health records data

Diabetes is increasing and early detection and treatment of complications is key to preventing the disease from getting worse. We have used automated retinal image analysis systems, which harness artificial intelligence, to analyse images of the back of the eye (i.e., of the retina). We have developed a model that accurately predicts cardiovascular disease from retinal images in community settings (which performs as well as established risk prediction models), but without the need for a blood test or blood pressure measurement. UK people with diabetes are offered annual eye screening which involves taking a digital image of the retina. We want to apply our methods to images from one of the largest Diabetic Eye Screening Programmes in the country, to see if retinal image feature assessment in combination with measures of diabetic control can predict complications for an individual better, to allow optimised review intervals and targeted prevention.