COVID-19 is showing few signs of running its course anytime soon, so health officials are likely to be concerned about pressure on hospital systems for the foreseeable future. A welcome development, then, could be a new technology that uses AI to help identify patients who are likely to require treatment in an intensive care unit.

Developed by researchers at the University of Waterloo and DarwinAI, an alumni-founded startup company, the tool uses AI to analyze more than 200 clinical data points, including vital signs, blood test results and medical history.

In a paper explaining the development of the tool, dubbed the COVID-Net Clinical ICU, that will be presented at the upcoming 2021 Conference on Neural Information Processing Systems, the team noted that they “conducted system-level insight discovery using a quantitative explainability strategy to study the decision-making impact of different clinical features and gain actionable insights for enhancing predictive performance. We further leveraged a suite of trust quantification metrics to gain deeper insights into the trustworthiness of COVID-Net Clinical ICU. By digging deeper into when and why clinical predictive models makes certain decisions, we can uncover key factors in decision making for critical clinical decision support tasks such as ICU admission prediction and identify the situations under which clinical predictive models can be trusted for greater accountability.”

The new AI software was trained using data from almost 400 cases at Hospital Sirio-Libanes in Sao Paulo, Brazil, in which doctors had decided if COVID patients should be admitted for intensive care.

“That is a very important step in the clinical decision support process for triaging patients and developing treatment plans,” said Alexander Wong, a professor of systems design engineering and Canada Research Chair in AI and Medical Imaging at Waterloo, in a statement. “The goal is to help clinicians make faster, more consistent decisions based on past patient cases and outcomes,” said Wong, a director of the Vision and Image Processing (VIP) Lab at Waterloo.

Rather than replacing doctors, the technology is meant to arm them with a new tool to make faster, more informed decisions and ensure the patients most in need of intensive care receive it.

“It’s all about augmenting their expertise to optimize the use of medical resources and individualize patient care,” Wong observed

The researchers have made the technology freely available so engineers and scientists around the world can work to help improve it, and they are now incorporating it into a larger clinical decision support system, developed in their ongoing COVID-Net open-source initiative, that also helps doctors detect COVID and determine its severity using AI analysis of medical images.

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