Artificial intelligence can improve how chest images are used in care of COVID-19 patients

According to a recent report by Johns Hopkins Medicine researchers, artificial intelligence (AI) should be used to expand the role of chest X-ray imaging—using computed tomography, or CT—in diagnosing and assessing coronavirus infection so that it can be more than just a means of screening for signs of COVID-19 in a patient’s lungs.

Within the study, published in the May 6 issue of Radiology: Artificial Intelligence, the researchers say that “AI’s power to generate models from large volumes of information—fusing molecular, clinical, epidemiological and imaging data—may accelerate solutions to detect, contain and treat COVID-19.”

Although CT chest imaging is not currently a routine method for diagnosing COVID-19 in patients, it has been helpful in excluding other possible causes for COVID-like symptoms, confirming a diagnosis made by another means or providing critical data for monitoring a patient’s progress in severe cases of the disease. The Johns Hopkins Medicine researchers believe this isn’t enough, making the case that there is “an untapped potential” for AI-enhanced imaging to improve. They suggest the technology can be used for:

  • Risk stratification, the process of categorizing patients for the type of care they receive based on the predicted course of their COVID-19 infection.
  • Treatment monitoring to define the effectiveness of agents used to combat the disease.
  • Modeling how COVID-19 behaves, so that novel, customized therapies can be developed, tested and deployed.

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