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"However, with medical images, observing and quantifying associations can often be hard because of the wide variety of features, patterns, colours, values and shapes that are present in real data". Instead, no one taught Google algorithms that some patterns in the retinas of those people were associated with an elevated risk of heart disease and stroke or high blood pressure.

With this alarming figure, the findings of Google AI is considered a breakthrough that could potentially save thousands of lives in the future.

Google's parent company Alphabet has more than just the search giant under its banner; alongside its freaky "X" experimental tech division sits its health science company Verily, which creates all manner of healthcare tech. According to the team, they were able to quantify the association between the retinal vessels and cardiovascular risks identified by researchers from previous medical studies. "They're taking data that's been captured for one clinical reason and getting more out of it than we now do", said Oakden-Rayner. More research would resolve whether the model needs to be adjusted for larger or smaller photos, and a larger data set than what the researchers used is more appropriate for deep learning. Discovering that we could do this is a good first step. These risk factors included gender, blood pressure, smoking habits and an estimate of age to within four years of a person's actual age. Google was surprised by the results and has pushed it further into predicting other CV risk factors.

Verily and Google scientists trained the algorithm by allowing it to analyse medical data from nearly 300,000 patients. According to her, the operational methodology of the algorithm can in future allow Google to generate a heatmap that shows which pixels were the most important elements for a predicting a specific CV risk factor.

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For example, the algorithm paid more attention to blood vessels for making predictions about blood pressure, as shown in the image above.

Google Research's deep learning work could represent a new method of scientific discovery.

When presented with retinal images of two patients, one of whom suffered a cardiovascular event in the following five years, and one of whom did not, Google's algorithm was able to tell which was which 70 percent of the time. "Rather than replacing doctors, it's trying to extend what we can actually do".

"To make this useful for patients, we will be seeking to understand the effects of interventions such as lifestyle changes or medications on our risk predictions and we will be generating new hypotheses and theories to test", Peng said.