Google's medical AI far less accurate at identifying illness in clinics than in the laboratory

A Google-developed AI that was capable of identifying cases of diabetic retinopathy (DR) with 90 percent accuracy in the testing laboratory has turned out to be much less useful in clinics and hospitals. In laboratory settings, the AI designed by Google Health performed at the equivalent level of a medical'specialist,' but in testing at 11 clinics in Thailand between November 2018 and August 2019, it was substantially less effective. The main challenge for researchers was the quality of images being fed to Google's AI, with 21 percent of the 1,838 photographs taken of patients graded as too low in quality to be processed because of inadequate lighting or unreliable photographic ability of the local clinic workers. Another challenge was slow internet speeds, which made the process of uploading and processing images time consuming. One clinic worker estimating they could only screen around 10 patients in a two hour window, according to a report in Newsweek.