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Building a slide deck, pitch, or presentation? By analysing scans of the back of a patient's eye, Verily software can predict their risk of heart disease.

In case you're wondering why Google and Verily chose retinal imaging for this breakthrough medical advancement, the rear interior wall of an eye called the fundus is jammed with blood vessels that reflect the body's overall health.

"Cardiovascular disease is the leading cause of death globally".

Apple late past year launched a heart study tied to its Apple Watch to see if it could detect and alert people to irregular heart rhythms that could be a sign of atrial fibrillation, a leading cause of stroke.

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He did not pitch in the playoffs that year, but went 1-0 with a 3.52 ERA over three postseason starts for Kansas City in 2014. That person also spoke on condition of anonymity because the deal was pending a physical and had not been announced.

Similar deep-learning technologies have exploded in the past five years and are widely used today in systems such as Google's image search and Facebook's facial recognition. These parameters could be used to predict if the person had a raised risk of heart disease or a cardiac event such as a heart attack. By studying their appearance with camera and microscope, doctors can infer things like an individual's blood pressure, age, and whether or not they smoke, all of which are crucial indicators of cardiovascular health.

However, deep learning techniques can also be used to increase the accuracy of diagnoses for these conditions, Peng wrote.

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.

For the study, the scientists developed deep learning models using retinal fundus images of almost 3, 00,000 people available from two countries; the United Kingdom and the U.S. and validated them using those from another 13,000 patients.

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And that's why everyone is assuming that the two countries are on a collision course to meet in the gold medal game in 2018. Canada came in to the tournament as an apparent underdog to the Americans. "I think that was a rash move to take it off".

The paper shows that deep learning can extract new knowledge from retinal fundus images and is able to identify cardiovascular risk factors.

According to Peng, the computer vision algorithm can distinguish between the retinal images of a smoker from that of a non-smoker at least seven out of 10 times. This can give clinicians greater confidence in the algorithm, and potentially provide new insights into retinal features not previously associated with cardiovascular risk factors or future risk.

Given the retinal image of one patient who later experienced a major cardiovascular event (such as a heart attack) and the image of another patient who did not, the algorithm could pick out the heart patient 70 per cent of the time.

With this in place, doctors can detect a patient's cardiovascular risk, as it doesn't require a blood test.

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Google also made sure to determine how the algorithm was making its prediction. All of these factors are important predictors of cardiovascular health.


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