New Tool Uses Deep-Learning AI Technology to Accurately Assess Severity of Lung Infections in COVID-19 Patients

The new work, part of the COVID-Net open-source initiative launched more than a year ago, involved researchers from the University of Waterloo (Waterloo, ON, Canada) and spin-off startup company DarwinAI (Waterloo, ON, Canada). Deep-learning AI was trained to analyze the extent and opacity of infection in the lungs of COVID-19 patients based on chest X-rays. Its scores were then compared to assessments of the same X-rays by expert radiologists.

For both extent and opacity, important indicators of the severity of infections, predictions made by the AI software were in good alignment with scores provided by the human experts. The researchers believe that the technology could give doctors an important tool to help them manage cases.

"Assessing the severity of a patient with COVID-19 is a critical step in the clinical workflow for determining the best course of action for treatment and care, be it admitting the patient to ICU, giving a patient oxygen therapy, or putting a patient on a mechanical ventilator," said Alexander Wong, a systems design engineering professor and co-founder of DarwinAI. "The promising results in this study show that artificial intelligence has a strong potential to be an effective tool for supporting frontline healthcare workers in their decisions and improving clinical efficiency, which is especially important given how much stress the ongoing pandemic has placed on healthcare systems around the world."

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