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Point-of-Care Ultrasound for COVID-19

Delivering real-time diagnosis of pneumonia caused by COVID-19.

Project Overview

Updated March 31, 2023

The Problem

Diagnosing COVID-19 in patients in rural and remote communities can be costly and time-consuming. As well, the molecular tests can fail to detect up to 30 per cent of cases.

The risks from delays or misdiagnosis can have severe consequences. Patients with false negative tests can unknowingly spread the infection, while delayed detection in long-term care home residents can lead to more outbreaks and deaths.

How We Are Solving It

The Intelligent Network for Point-of-Care Ultrasound for COVID-19 project aims to improve our ability to detect COVID-19 by developing an AI-powered platform that can be used with wireless, handheld ultrasound devices. Combined with machine learning and a cloud-based platform, this technological advance will deliver real-time diagnosis of patients with pneumonia, potentially caused by COVID-19.

Led by Providence Health Care in partnership with Clarius, Change Healthcare, Rural Coordination Centre of BC, the University of British Columbia and Vancouver Coastal Health, the project’s goal is to make the networked, portable ultrasound technology available in rural and remote communities, and eventually long-term care homes for seniors.

By deploying this device during an outbreak, tests can be performed repetitively without adverse effects to the patients. It also reduces unnecessary exposure of healthcare workers and the need for potentially infected individuals to travel to a test site.

The Result

This project is an augmentation of the Intelligent Network Point-of-Care Ultrasound project and aims to use a handheld ultrasound device powered by artificial intelligence to provide real-time diagnosis of patients with pneumonia, potentially caused by COVID-19. The project developed novel artificial intelligence to perform on par with clinical experts for identification of lung pathology, including some of the ultrasound image features of COVID-19. Frontline workers, particularly in rural and remote areas, were supported through the development of virtual training, remote clinical support, and artificial intelligence tools to rapidly identify COVID-19 lung abnormalities and provide a clinical decision support tool.






Project Lead

  • providence healthcare

Project Partners

  • change healthcare
  • clarius web
  • rcc bc
  • dts ubc logo e1632687012996
  • van coastal

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