Algorithm assesses risk by scanning patient’s eyes
A newly published study in the journal Nature Biomedical Engineering reveals how scientists from the two firms use an AI algorithm to accurately identify a patient’s blood pressure, age and whether they smoke, by analysing a scan of the back of their eye.
The programme then combines the information in order to evaluate the patient’s risk of suffering a major cardiac event such as a heart attack, The Verge reports.
Luke Oakden-Rayner, a medical researcher at the University of Adelaide who specialises in machine learning analysis, told the website that the AI algorithm could improve existing analytic tools in the industry.
“They’re taking data that’s been captured for one clinical reason and getting more out of it than we currently do,” he said. “Rather than replacing doctors, it’s trying to extend what we can actually do.”
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But the study “isn't without limitations”, says Engadget, as the scientists “only surveyed eye images with a 45-degree field of view”.
Further research will help determine whether the programme needs to be adjusted to analyse larger or smaller images, the website adds, while a “larger data set” would help improve the AI system’s accuracy.
“In other words, it’s not yet ready for clinical testing, but it’s a promising start for non-invasive evaluation of cardiovascular health,” Engadget concludes.
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