Researchers Amass Lung Scans to Build AI Systems for Patient Care

Monday, July 27, 2020 - 14:19

Researchers have stated that they can begin to build more reliable AI models that seek to predict the severity of disease, gauge patients’ response to various treatments, and determine whether they are likely to need a ventilator or transfer to an intensive care unit.

Radiologists said demand for such AI-powered tools may increase significantly in the months ahead, as surging numbers of infections threaten to strain medical resources in the United States and around the globe, STAT News reports.

“If this hangs around, having (AI) to help triage cases could be valuable,” said Bibb Allen, chief medical officer for the data science institute at the American College of Radiology. “But we’ve got to build it first. That’s kind of where we are.”

Multiple AI teams have formed within the University of California. On its San Diego campus, a research team worked with Amazon Web Services to train an AI to spot early signs of pneumonia, a common cause of death in Covid-19 patients. The system, which analyzes chest X-rays, is not intended to diagnose Covid-19, but to flag patients that may become severely ill.

“Algorithms in imaging are becoming pretty effective,” said Christopher Longhurst, a physician and chief information officer at the University of California, San Diego. "But the question is how you really implement them in a way that really helps doctors and patients.”

That is the biggest challenge facing AI in the treatment of Covid-19 and many other conditions. AI models often appear to perform well in carefully structured experiments, but the real test comes when they are deployed in actual patient care, where they must be able to perform consistently across diverse groups of patients and deliver information to doctors in a way that’s compatible with their computer systems and work routines.


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