Ayyy-EYE! Google code 'predicts heart disease' by eyeballing retinas

AI researchers at Google have developed algorithms that can assess the risk of heart attacks by analyzing retinal scans. By looking for common patterns in images of retinal scans and matching them up with the data in the patients' medical records, one algorithm could determine if someone was a smoker or non-smoker to an accuracy of 71 per cent. Another algorithm focused on the blood vessels in the eye could tell if someone had severe high blood pressure or not, a sign associated with increased chances of stroke. Their models can also predict other factors such as age, gender, and the chance of a heart attack or stroke, the boffins claim in a paper published in Nature Biomedical Engineering journal on Monday. "Given the retinal image of one patient who (up to 5 years) later experienced a major [cardiovascular] event (such as a heart attack) and the image of another patient who did not, our algorithm could pick out the patient who had the cardiovascular event 70% of the time," Lily Peng, a product manager at Google Brain, explained in a blog post this week.