Google’s AI predicts heart disease
Representative Image

Researchers at Google have discovered a new way to assess a person’s risk of heart disease through eye scans using artificial inteligence.

In a paper published in Nature’s Biomedical Engineering journal (PDF), the search giant’s health subsidiary Verily detailed a method to predict risks of heart diseases that uses by scanning the rear interior wall of your eye.

Through the scanning of the back of the patient’s eye, the company’s software is able to accurately deduce data, including an individual’s age, blood pressure, and whether or not they smoke. This can then be used to predict their risk of suffering a major cardiac event — such as a heart attack with roughly the same accuracy as current leading methods.

Two images of the fundus, or interior rear of your eye. The one on the left is a regular image; the on the right shows how Google’s algorithm picks out blood vessels (in green) to predict blood pressure. Photo by Google / Verily Life Sciences

To train the algorithm, Google and Verily’s scientists used machine learning to analyze a medical dataset of nearly 300,000 patients. This information included eye scans as well as general medical data. As with all deep learning analysis, neural networks were then used to mine this information for patterns, learning to associate telltale signs in the eye scans with the metrics needed to predict cardiovascular risk (e.g., age and blood pressure).

Now it does seem a bit strange 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. That being said, we’re probably quite a long way off from this becoming the standard of checking on our heart health, but it does sound pretty promising.


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