Without the help of an optometrist
In the USA, for the first time, AI was allowed to diagnose people without the participation of doctors
Anatoly Alizar, Geektimes
The US Food and Drug Administration (FDA) has made a historic decision, for the first time allowing Artificial Intelligence to independently conduct a medical examination of people without the participation of a live specialist.
The FDA has granted permission to IDx, which is developing the IDx-DR diagnostic system for ophthalmology. As stated in the manufacturer's materials, the device works under AI control.
The IDx-DR software recognizes the signs of diabetic retinopathy from the photos of the eye. This is a widespread complication in diabetes that affects the vessels of the retina of the eyeball. It is observed in 90% of patients with diabetes mellitus and can lead to vision loss.
The program uses an AI algorithm that analyzes photos taken by a special Topcon NW400 device for photographing the retina. A doctor or nurse uploads photos to a cloud server or a local computer – and in less than 1 minute the program returns a positive or negative diagnostic result.
In case of a negative result, the next examination is scheduled after 12 months, and in case of a positive result, the patient is referred to a specialist.
The standard procedure still involves human involvement: a trained operator must take pictures and upload them to the cloud. But it can be any clinic employee, technician or trainee, not an ophthalmologist. The diagnosis of diabetic retinopathy is performed without the participation of a single person who understands this disease. Specialists are not required either at the time of the examination or for subsequent interpretation of the results. If the results are negative, then the ophthalmologist will not even see the pictures taken.
Before issuing the permit, the FDA evaluated the results of clinical trials on 900 diabetic patients from ten clinics. The system showed 87.4% accuracy in identifying patients with a minor degree of diabetic retinopathy, and 89.5% accuracy for patients with complications requiring treatment.
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