A team from University of California, San Francisco (UCSF) has demonstrated promising potential in using a smartphone camera to diagnose type 2 diabetes. The innovative research demonstrates a technique that needs no additional hardware other than a functional smartphone camera, and currently is more than 80 percent accurate in detecting diabetes.
“Diabetes can be asymptomatic for a long period of time, making it much harder to diagnose,” says lead author on the new study, Robert Avram. “To date, noninvasive and widely-scalable tools to detect diabetes have been lacking, motivating us to develop this algorithm.”
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