Google AI can scan your eyes to predict heart disease

Google AI-can-predict-cardiovascular-problems

In a paper published in the Nature journal Biomedical Engineering, the project researchers said that the method would have to be subject to further testing before it can be used in clinical settings.

The company's latest approach with AI predicting heart disease could build on doctors' current abilities by providing a tool that people could one day use to quickly and easily screen themselves for health risks that can contribute to heart disease, which is the leading cause of death worldwide.

Harlan Krumholz of Yale University who was not involved in the research believes technology could soon "turbo-charge" diagnosis. "And one avenue is to empower people with rapid ways to get useful information about their health".

In the gray retinal image used by the deep-learning algorithm, blood pressure is highlighted in shades of green. This includes the person's gender, smoking status, blood pressure, and age. Those eye scans helped train the networks on which tell-tale signs led to indicate long-term cardiovascular risk. Other disease factors such as diabetes significantly increases risk.

Research states that the rear interior wall of the eye (the fundus) is chock-full of blood vessels that reflect the body's overall health. Using attention techniques, the researchers generated a heatmap that showed which pixels were the most important for predicting a specific cardiovascular risk factor.

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The tech predicts risk while being noninvasive, fast, and convenient.

However, while Google's algorithms did manage to approach the accuracy of current methods, it was still far from flawless.

Training deep-learning models on data from more than a quarter of a million patients, the scientists were able to predict the cardiovascular risk factors that were not previously thought to be present in retinal fundus images. What's interesting is that the blog entry claimed that the algorithm could detect whether the patient smoked or not and assess their systolic blood pressure based on image analysis. This is a feat mostly unique to AI, to be sure; while some human doctors may have dealt with enough heart disease patients and potentials to be able to spot some telltale signs, it took Google's machine 284,335 sets of eyes' worth of training to attain its expertise, essentially making it better than any human at this kind of prediction.

A new study by Google and its health-focused Alphabet-sibling, Verily Life Sciences, has shown that deep-learning algorithms can accurately predict heart disease by analyzing photographs of a individual's retina.

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