Researchers at the University of Washington have developed BiliScreen, an app designed to offer pancreatic cancer screening by having users take photos of themselves with a smartphone.
BiliScreen detects elevated bilirubin levels in the white part of the user's eye by employing a smartphone camera, computer vision algorithms, and machine learning tools.
Using the smartphone's built-in camera and flash, BiliScreen collects images of a person's eye as they take a selfie. The computer-vision system then isolates the eye's sclera, and BiliScreen calculates the sclera's color information and correlates it with bilirubin levels via machine learning algorithms.
The app correctly identified cases of concern in an initial clinical study of 70 people with 89.7% accuracy, compared to the blood test currently used.
BiliScreen will be presented next month at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2017) in Hawaii.
From UW News
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