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AI Case Study

IDX launched the first FDA approved artificial intelligence service that can diagnose the eye disease diabetic retinopathy without a clinician's involvement

Millions suffer from diabetic retinopathy as they do not see their eye doctor regularly. The FDA approved a solution from IDx that allows health care providers with minimal training to scan patients retinas. An algorithm then determines if it recommends that a patient see an eye specialist. To meet the FDA approval the algorithm needed to predict at least 82.5% of patients who did not have the disease. The device was better than 87% accurate.



Healthcare Equipment And Supplies

Project Overview

"The software, called IDx-DR, looks for diabetic retinopathy, an eye disease that afflicts individuals with diabetes. With minimal training, health care providers can use a special camera to take a picture of the back of the patient’s retina, which an algorithm then analyzes to look for the disease. If the software finds evidence of the disease, it recommends that a patient see an eye specialist."

Reported Results

To meet FDA approval "the algorithm needed to correctly identify at least 85 percent of patients who did have the disease, and needed to correctly identify at least 82.5 percent of patients who did not have the disease. This device passed the bar, with rates of 87.4 and 89.5 percent, respectively. Human ophthalmologists error rate is 20 - 30% when looking at digital images.


Likely Convolutional Neural Networks (CNN) for analysing images.


R And D

Product Development


"Early detection of retinopathy is an important part of managing care for the millions of people with diabetes, yet many patients with diabetes are not adequately screened for diabetic retinopathy since about 50 percent of them do not see their eye doctor on a yearly basis."

"A computer program that can analyze medical images could save time and money, cutting down on unnecessary, expensive trips to could be used by primary care physicians or other medical professionals who are not eye specialists."



Medical patient images

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