AI technology can assess severity of COVID-19 with promising degree of precision

Artificial intelligence (AI) technology developed by researchers at the University of Waterloo is able to assess the severity of COVID-19 cases with a promising degree of precision.

A study, which is part of the open-source COVID-Net initiative launched over a year ago, involved researchers from Waterloo and the start-up DarwinAI, as well as radiologists from the Stony Brook School of Medicine and Montefiore. New York Medical Center.

Deep learning AI was trained to analyze the extent and opacity of infection in the lungs of patients with COVID-19 based on chest x-rays. His scores were then compared to evaluations of the same x-rays by expert radiologists.

For the extent and opacity, important indicators of the severity of infections, the predictions made by the AI ​​software were in good alignment with the scores provided by human experts.

Alexander Wong, professor of systems design engineering and co-founder of DarwinAI, said 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 to determine the best course of action for treatment and care, whether it is to admit the patient in the ICU, administer oxygen therapy to a patient, or place a patient on a mechanical ventilator. “

Alexander Wong, Professor of Systems Design Engineering and Co-Founder, DarwinAI

“The promising results of this study show that artificial intelligence has great potential to be an effective tool to support frontline healthcare workers in their decisions and improve clinical efficiency, which is particularly important given the stress that the current pandemic has placed on health systems. the world.”

Source:

Journal reference:

Wong, A., et al. (2021) Towards a Computer Assisted Gravity Assessment Using Deep Neural Networks for Scoring the Geographic Extent and Opacity of Chest X-rays of SARS-CoV-2. Scientific reports. doi.org/10.1038/s41598-021-88538-4.

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