In a study published on Monday in the journal Nature Biomedical Engineering, Google AI researchers described how deep learning algorithms can be trained to predict heart disease symptoms by looking at retinal images.
"Traditionally, medical discoveries are often made through a sophisticated form of guess and test - making hypotheses from observations and then designing and running experiments to test the hypotheses", wrote Peng.
"Our approach uses deep learning to draw connections between changes in the human anatomy and disease, akin to how doctors learn to associate signs and symptoms with the diagnosis of a new disease", Peng said.
Doctors usually take into account various risk factors for patient assessment such as some genetic data (like age and sex) and data related to lifestyle components (such as a smoking and blood pressure). What's more, the new system shows what parts of the eye image lead to successful predictions, giving researchers new leads into what causes cardiovascular disease. 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.
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"They're taking data that's been captured for one clinical reason and getting more out of it than we now do", Luke Oakden-Rayner, a medical researcher from the University of Adelaide, told The Verge.
Recent estimates point that India has world's most heart failure deaths at 23%, and according to Indian Heart Association, 50% of all heart attacks in Indians happen to those under 50 years of age and 25% of all heart attacks in Indians happen to those under 40.
Google researchers hope to ideal this method and machine further so that it could analyse the present data more accurately without the aid or direction of humans.
"They're taking data that's been captured for one clinical reason and getting more out of it than we now do", he said. Discovering that we could do this is a good first step.
"We opened the black box by using attention techniques to look at how the algorithm was making its prediction".
That said, it's clear that artificial intelligence and machine learning have the potential to bring added convenience and affordability to the healthcare industry, even in areas as small as our eyes.