Scientists Create Algorithm That Uses Routine Eye Scans to Identify Heart Attack Risk With Accuracy of 70%-80%:
Scientists have developed an artificial intelligence system that can analyze eye scans taken during a routine visit to an optician or eye clinic and identify patients at a high risk of a heart attack. Doctors have recognized that changes to the tiny blood vessels in the retina are indicators of broader vascular disease, including problems with the heart. In the research, led by the University of Leeds, deep learning techniques were used to train an AI system to automatically read retinal scans and identify those people who, over the following year, were likely to have a heart attack. During the deep learning process, the AI system analyzed the retinal scans and cardiac scans of more than 5,000 people. The AI system identified associations between pathology in the retina and changes in the patient’s heart. Once the image patterns were learned, the AI system could estimate the size and pumping efficiency of the left ventricle, one of the heart’s four chambers, from retinal scans alone. An enlarged ventricle is linked with an increased risk of heart disease. With information on the estimated size of the left ventricle and its pumping efficiency combined with basic demographic data about the patient, their age, and sex, the AI system could predict their risk of a heart attack over the subsequent 12 months.