Artificial intelligence can detect heart attack from eye scan

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A retinal scan, courtesy of UK Biobank

K V Venkatasubramanian

Scientists have developed an artificial intelligence system that can analyse eye scans taken during a routine visit to an optician or eye clinic and identify patients at a high risk of a heart attack.
The international team of doctors has recognized that changes to the tiny blood vessels in the retina are indicators of broader vascular disease, including problems with the heart.
Deep learning techniques were used in the research, led by the University of Leeds, 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.
Deep learning is a complex series of algorithms that enable computers to identify patterns in data and to make predictions. The researchers have reported their findings in the journal Nature Machine Intelligence.
They said that the AI system had an accuracy of between 70% and 80% and could be used as a second referral mechanism for in-depth cardiovascular examination. It could also be used to track early signs of heart disease.
Dr Chris Gale, professor of Cardiovascular Medicine at the University of Leeds, and an author, said: “The AI system has the potential to identify individuals attending routine eye screening who are at higher future risk of cardiovascular disease, whereby preventative treatments could be started earlier to prevent premature cardiovascular disease.”
The use of deep learning in the analysis of retinal scans could revolutionize the way patients are regularly screened for signs of heart disease.
Prof Alex Frangi, also from the University of Leeds, said this technique opens up the possibility of revolutionizing the screening of cardiac disease. “Retinal scans are comparatively cheap and routinely used in many optician practices. As a result of automated screening, patients who are at high risk of becoming ill could be referred for specialist cardiac services.”
He said that the system could also be used to track early signs of heart disease.
Chris Gale, Professor of Cardiovascular Medicine at the University of Leeds and a Consultant Cardiologist at Leeds Teaching Hospitals NHS Trust, was one of the authors of the research paper.
He said: “The AI system has the potential to identify individuals attending routine eye screening who are at higher future risk of cardiovascular disease, whereby preventative treatments could be started earlier to prevent premature cardiovascular disease.”

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