Synced It's All in the Eyes: Google AI Calculates Cardiovascular Risk From Retinal Images

A retinal fundus image is a photograph of the back of the eye taken through the pupil. For more than 100 years these images have been used for detecting eye disease. Now Google has introduced a surprising new use for retinal images: combined with artificial intelligence, they can also predict a patient's risk of heart attack or stoke. Research arm Google Brain today published a paper in the journal Nature Biomedical Engineering which demonstrates how deep learning models can use retinal images to detect a patient's age, gender, smoking status and systolic blood pressure; calculate cardiovascular risk factors; and predict the risk of major adverse cardiac events occurring over the next five years. A problem with today's mainstream cardiovascular risk calculators such as the Pooled Cohort Equations, Framingham, and Systematic Coronary Risk Evaluation is that they require the input of multiple features such as blood pressure, body mass index, glucose and cholesterol levels, etc. to generate a disease risk result. A study by the American College of Cardiology's Practice Innovation And Clinical Excellence Program concluded that the data required to calculate 10-year risk was available for less than 30% of patients.