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

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

Using this information, it's then possible to assess someone's risk of suffering a heart attack or developing heart disease. This could be a useful screening tool for doctors. He added that this should not be seen as a replacement for diagnostic tests and clinical judgement but merely an analyser that would be an extension of the diagnostic armament. "However, with medical images, observing and quantifying associations can be hard because of the wide variety of features, patterns, colors, values and shapes that are present in real images", researchers noted in a paper (PDF) published in the Nature journal Biomedical Engineering on Tuesday.

The scientists trained deep-learning models on data gathered from over 250,000 patients. Typically, this assessment includes examining risk factor such as age, sex, smoking, blood pressure, and cholesterol, as well as taking into account whether the patient has another disease associated with increased risk of cardiovascular issues, such as diabetes.

Google is betting on established research on building this algorithm.

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Already, the model has a 70% accuracy rate in predicting whether a person will suffer a cardiac event within five years.

"Using deep-learning algorithms trained on data from 284,335 patients, we were able to predict cardiovascular risk factors from retinal images with surprisingly high accuracy for patients from two independent datasets of 12,026 and 999 patients", writes Google Brain Team product manager Lily Peng.

Experts believe that this is a credible study mainly because the science behind the hypothesis is sound. 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.

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Google's parent company Alphabet has more than just the search giant under its banner; alongside its freakish "X" experimental tech division sits its health science company Verily, which creates all manner of healthcare tech.

The true power of this kind of technological solution is that it could flag risk with a fast, cheap and noninvasive test that could be administered in a range of settings, letting people know if they should come in for follow-up. In future large data sets could provide deeper insight.

The study isn't without limitations, given that it only surveyed eye images with a 45-degree field of view. Researchers are trying to correct this problem with new versions. Michael V McConnell, head of Cardiovascular Health Innovations at Verily, said that the research needs more work and a larger patient database to validate these findings before it's ready for clinical testing.

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