Algorithm Spots COVID-19 Cases from Eye Images: Preprint

A small study shows artificial intelligence can pick out individuals with coronavirus infections, but ophthalmologists and AI experts say the approach is far from proven to be capable of distinguishing infections with SARS-CoV-2 from other ills.

anthony king
| 4 min read
covid-19 coronavirus sars-cov-2 pandemic eyes conjunctivitis artificial intelligence machine learning

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ABOVE: Eye regions analyzed by the AI-based tool for screening potential coronavirus infections
YANWEI FU

Scientists describe a potential screening method for COVID-19 based on eye images analyzed by artificial intelligence. Scanning a set of images from several hundred individuals with and without COVID-19, the tool accurately diagnosed coronavirus infections more than 90 percent of the time, the developers reported in a preprint posted to medRxiv September 10.

“Our model is quite fast,” Yanwei Fu, a computer scientist at Fudan University in Shanghai, China, who led the study, tells The Scientist. “In less than a second it can check results.”

Currently, screening for coronavirus infection involves CT imaging of the lungs or analyzing samples from the nose or throat, both of which take time and require professional effort. A system based on a few images of the eyes that could triage or even diagnose people would save on both costs and ...

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Meet the Author

  • anthony king

    Anthony King

    Anthony King is a freelance science journalist based in Dublin, Ireland, who contributes to The Scientist. He reports on a variety of topics in chemical and biological sciences, as well as science policy and health. His articles have appeared in Nature, Science, Cell, Chemistry World, New Scientist, the Irish Times, EMBO Reports, Chemistry & Industry, and more. He is President of the Irish Science & Technology Journalists Association. 

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