SOUTH SAN FRANCISCO, Calif.—The eyes are the windows to the soul, according to a much quoted aphorism. Now, medical researchers are finding that eyes can also provide a window that allows them to see if a patient is at risk for cardiovascular disease. Scientists from Google and its health-tech subsidiary Verily recently announced that they have been using a type of artificial intelligence (AI) known as deep learning to identify signals of this disease. The results of their research, published in February in Nature Biomedical Engineering, “Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs via Deep Learning,” shows promising findings on the application of machine learning in identifying risk markers through non-invasive means.


On the left is a sample retinal image from the dataset in color. On the right is an attention map indicating areas that support the prediction for high systolic blood pressure in green, which overlap with the retinal blood vessels.
The paper demonstrates that deep learning applied to a retinal fundus image, a photograph that includes the blood vessels of the eye, can frequently predict these risk factors—from smoking status to blood pressure—as well as predict the occurrence of a future major cardiovascular event on par with current measures, according to one of the authors, Michael V. McConnell, MD, MSEE, head of Cardiovascular Health Innovations, Verily.

“One of the exciting aspects of this study is the generation of ‘attention maps’ to show which aspects of the retina contributed most to the algorithm, thus providing a window into the “black box” often associated with machine learning,” Dr. McConnell said in a Verily blog post. “This can give clinicians greater confidence in the algorithm, and potentially provide new insights into retinal features not previously associated with cardiovascular risk factors or future risk.”