Google's new AI algorithm predicts heart disease by looking at your eyes

Google Scientists Create Algorithm For Heart Attack Risk Based On Retinal Scans

A simple eye scan could screen for heart disease, research has shown.

Verily Life Sciences LLC, the health division of Google Inc.'s parent company Alphabet Inc., today detailed the results of its work applying machine learning to retinal images to identify the risk factors of cardiovascular disease. With its system, Google's deep learning tech is able to predict cardiovascular risk in any given individual simply using images of their retina. They are also showing promise in other arenas of health, including by looking for signs of cancer in the X-ray scans reviewed by radiologists.

The study was published in Nature Biomedical Engineering, and Google Brain Team Product Manager Lily Peng, one of the researchers behind the study, also wrote up a blog entry on the study for Google Research.

Now it does seem a bit odd that eye-scanning could be a way to judge the health of your heart, but this is based on established research where the rear interior wall of your eye is packed with blood vessels that can reflect your body's overall health. Through mass aggregation and deep learning, an AI program was able to accomplish this feat, and will only continue to improve as it is further trained, tested, and perhaps eventually used in the real world.

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Two images of the fundus, or interior rear of your eye. This data is then used to predict the likelihood of the risk of the patient suffering from a heart attack or other major cardiac event with nearly the same accuracy as the current methods employed by doctors today. Current predictions - which require blood tests - operate with 72 percent accuracy. One of the problems with this study was that it could look at eye images at 45 degree views and this could miss out vital zones in the retina. If the algorithm's success rate grows and Google is able to fine-tune the technology, then it's possible that the method could become be a quicker and cheaper way to discover at-risk patients.

Maulik Majmudar, associate director of the Healthcare Transformation Lab at Massachusetts General Hospital, told the Post that age and gender are already good predictors of risk for such disease.

The researchers tested the algorithm on a set of scans from about 12,000 patients, roughly 100 of whom had a heart attack within five years following their retinal imaging.

Artificial intelligence could speed up existing forms of medical analysis, but before he can be trusted, the algorithm needs to undergo additional testing.

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