Smartphone Cameras Can Now Detect Diabetes with 80 Percent Accuracy
upstart writes in with an IRC submission:
Smartphones May Help Detect Diabetes:
"The ability to detect a condition like diabetes that has so many severe health consequences using a painless, smartphone-based test raises so many possibilities," said co-senior author Geoffrey H. Tison, MD, MPH, assistant professor in cardiology, of the Aug. 17, 2020, study in Nature Medicine. "The vision would be for a tool like this to assist in identifying people at higher risk of having diabetes, ultimately helping to decrease the prevalence of undiagnosed diabetes."
[...] In developing the biomarker, the researchers hypothesized that a smartphone camera could be used to detect vascular damage due to diabetes by measuring signals called photoplethysmography (PPG), which most mobile devices, including smartwatches and fitness trackers, are capable of acquiring. The researchers used the phone flashlight and camera to measure PPGs by capturing color changes in the fingertip corresponding with each heartbeat.
In the Nature Medicine study, UCSF researchers obtained nearly 3 million PPG recordings from 53,870 patients in the Health eHeart Study who used the Azumio Instant Heart Rate app on the iPhone and reported having been diagnosed with diabetes by a health care provider. This data was used to both develop and validate a deep-learning algorithm to detect the presence of diabetes using smartphone-measured PPG signals.
[...] "We demonstrated that the algorithm's performance is comparable to other commonly used tests, such as mammography for breast cancer or cervical cytology for cervical cancer, and its painlessness makes it attractive for repeated testing," said study author Jeffrey Olgin, MD, a UCSF Health cardiologist and professor and chief of the UCSF Division of Cardiology. "A widely accessible smartphone-based tool like this could be used to identify and encourage individuals at higher risk of having prevalent diabetes to seek medical care and obtain a low-cost confirmatory test."
Journal Reference:
Robert Avram, et al. A digital biomarker of diabetes from smartphone-based vascular signals. Nat Med (2020). DOI: https://doi.org/10.1038/s41591-020-1010-5
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