Artificial Intelligence Algorithm Analyzes Chest X-Rays to Detect COVID-19 in Seconds

A team of researchers at the University of Minnesota (Minneapolis, MN, USA) recently developed and validated an artificial intelligence (AI) algorithm that can evaluate chest X-rays to diagnose possible cases of COVID-19.

Working together with M Health Fairview and Epic, the algorithm will be available at no cost to other health systems through Epic, the medical records software used by many health care organizations across the country. When a patient arrives in the emergency department with suspected COVID-19 symptoms, clinicians order a chest X-ray as part of standard protocol. The algorithm automatically evaluates the X-ray as soon as the image is taken. If the algorithm recognizes patterns associated with COVID-19 in the chest X-ray - within seconds - the care team can see within Epic that the patient likely has the virus.

To develop the algorithm, the team analyzed de-identified chest X-rays taken at M Health Fairview since January. To train it to diagnose COVID-19, the team used 100,000 X-rays of patients who did not have COVID-19 and 18,000 X-rays of patients who did. Once the team validated the algorithm, the team built the infrastructure around the algorithm, designing it to seamlessly and immediately translate the algorithm’s findings into the medical record software and notify care teams. The researchers have decided to make their algorithm available free of charge in the Epic App Orchard for more than 450 health care systems worldwide.

“This may help patients get treated sooner and prevent unintentional exposure to COVID-19 for staff and other patients in the emergency department,” said Christopher Tignanelli, MD, assistant professor of surgery at the University of Minnesota Medical School and co-lead on the project. “This can supplement nasopharyngeal swabs and diagnostic testing, which currently face supply chain issues and slow turnaround times across the country.”

“The power of modern AI and computer vision is precise, and automatic extraction of effective visual patterns from imaging data enables rapid decision-making. Our model learns from thousands of X-rays and detects COVID-19 in seconds, then immediately shows the risk score to providers who are caring for patients,” said Ju Sun, PhD, assistant professor at the U of M College of Science and Engineering, who was part of the project.

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