Google Can Predict Heart Disease By Looking Into Your Eyes

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Google's scientists and its health-tech subsidiary, Verily have revealed that analysing scans of the back of an individual's eye can help detect the risk of heart disease. The rear interior wall of the eye is full of blood vessels that reflect the body's overall health.

"Most cardiovascular risk calculators use some combination of these parameters to identify patients at risk of experiencing either a major cardiovascular event or cardiac-related mortality within a pre-specified time period, such as 10 years", the paper states.

The researchers conclude that their results "indicate that the application of deep learning to retinal fundus images alone can be used to predict multiple cardiovascular risk factors".

The researchers trained deep learning algorithms on data from thousands of patients recorded in a massive United Kingdom study, which was used with retinal scans to produce a program that can identify risk factors from the scan information alone.

The "smart" system already has a precision of about 70% predicting who will suffer a heart attack or other serious cardiovascular event within the next five years. Scientists have used a machine learning to analyse a medical dataset of almost 30,000 patients. Google recently presented its findings in the online medical journal Nature Biomedical Engineering. Heart disease is now the leading cause of death worldwide. Eye scans data as well as general medical data was included in the analysis.

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Lily Peng, a doctor and lead researcher on the project, says Google was surprised by the results.

Your eyes really are the windows to your soul, or at least your heart.

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.

However, Google cautions that more research needs to be done. Also, the notion of using retinal scans to predict cardiac issues is not unfounded, as conditions such as diabetes and high blood pressure can cause significant changes to an individual's retina. The researchers said that the method is needed to be tested more thoroughly before it can be used for clinical testing.

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