Heart attack, stroke, predicted via retinal images

Google’s Lily Peng has developed an algorithm that can predict heart attacks and strokes by analyzing images of the retina.

The system also shows which eye areas lead to successful predictions, which can provide insight into the causes of cardiovascular disease.

The dataset consisted of 48,101 patients from the UK Biobank database and 236,234 patients from EyePACS database.  A study of  12,026 and 999 patients showed a high level of accuracy:

-Retinal images of a smoker from a non-smoker 71 percent of the time, compared to a ~50 percent human  accuracy.

-While doctors can typically distinguish between the retinal images of patients with severe high blood pressure and normal patients, Google AI’s algorithm predicts the systolic blood pressure within 11 mmHg on average for patients overall, including those with and without high blood pressure.

-According to the company the algorithm predicted direct cardiovascular events “fairly accurately, ” statin that “given the retinal image of one patient who (up to 5 years) later experienced a major CV 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 CV event 70% of the time. This performance approaches the accuracy of other CV risk calculators that require a blood draw to measure cholesterol.”

According to Peng: “Given the retinal image of one patient who (up to 5 years) later experienced a major CV 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 CV event 70 percent of the time, This performance approaches the accuracy of other CV risk calculators that require a blood draw to measure cholesterol.”


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