A novel pairing of two technologies may offer a solution for better screening for diabetic retinopathy, a condition that can lead to permanent vision loss if not caught early. Combining a smartphone-mounted device that takes high-quality retinal pictures with artificial intelligence software that reads them can determine in real time whether a patient should be referred to an ophthalmologist for follow up.

Yannis M. Paulus, MD, with the device. (Credit: University of Michigan)

The RetinaScope device uses utilizes a proprietary deep neural network software platform called EyeArt. After pupillary dilation, the scope was used to image patient retinas and the images were analyzed with the software, which graded them as referral-warranted diabetic retinopathy (RWDR) or non-referral-warranted DR.

Slit-lamp evaluation confirmed RWDR in 53 subjects (76.8 percent). Automated interpretation had a sensitivity of 86.8 percent (above the 80 percent recommended for an ophthalmic screening device) and specificity of 73.3 percent.

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