In the US, about 630,000 Americans die from heart disease each year. That’s one in every four deaths. Locally, about one in 12 or 2.4 million Canadian adults age 20 and over live with diagnosed heart disease. Twelve Canadian adults die every hour from this dreaded disease.
This is indeed a severe problem, not just for Canada but also the world.
Being able to diagnose heart disease early helps to treat and control it. Now, being able to predict a person’s risk of heart disease in advance will help save many lives. And that’s the point where we are about to reach.
By using machine learning, scientists from Google have found a new way to predict a person’s risk of heart disease. By examining the scans of the back of a patient’s eye, they can be able to accurately deduce data, like the person’s age, blood pressure, and whether or not they smoke. This information can then be used to predict that individual’s risk of suffering a major cardiac attack.
This type of assessment is done without the need for a blood test which makes it easier and faster for doctors to analyze a patient’s cardiovascular risk.
This, of course, is still in the testing phase and will need some more work to be done. But given the scientists have reached this point, it is a huge breakthrough, to predict a person’s risk for heart disease by scanning the eye.
The idea of looking at your eyes to judge your health is one that sounds a bit unusual, but it does make sense. Think about when you are sick with the flu, by looking in the mirror you can tell that your eyes are not that sparkly and alert. The eyes say a lot, and similarly, they can tell about our health.
By studying the rear interior wall of the eye, where blood vessels are, scientists can tell about the body’s overall health. By examining the eyes appearance with a camera and microscope, doctors can judge things like the blood pressure, age, and if the person is a smoker. These are all important in predicting our cardiovascular health.
During the testing phase, the scientists on examining two retinal images of two different patients, one of whom who will suffer from a cardiovascular event in the following five years, and one of whom will not, the Google’s algorithm was able to tell which was which 70 per cent of the time. This is not much different from the commonly used SCORE method, which requires a blood test and makes correct predictions at 72 per cent of the time.
The Google’s method that the scientists are using is not far off and what’s more appealing is that there is no need for a blood test.
Another significant thing that is noteworthy is that this work opens up more than just a new method of judging cardiovascular risk. It points the way toward new AI-powered predictions that can be used in the medical field to help detect from an early stage our health risks.
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