Artificial intelligence deployment in diabetic retinopathy: the last step of the translation continuum

Abstract

The disproportionate burden of diabetes worldwide on low-income and middle-income countries (LMICs) is a predicament keenly felt in the field of ophthalmology.1 Globally, the prevalence of visual impairment due to diabetic retinopathy is rising,2 attributed to growing rates of diabetic macular oedema, which is now more common than the historically more feared proliferative diabetic retinopathy and is the predominant cause of moderate or severe vision loss in patients with diabetes.3 Blindness from diabetic retinopathy is rendered all the more poignant by well established data about its preventability with early detection and intervention.

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