Point of Care Heart-Lung Imaging for Patients Presenting with COVID-19 Symptoms: Artificial Intelligence Precision Modeling for Prediction of Outcomes
- Funded by Canadian Institutes of Health Research (CIHR)
- Total publications:0 publications
Grant number: 202005VR2
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Key facts
Disease
COVID-19Start & end year
20202021Known Financial Commitments (USD)
$195,244.5Funder
Canadian Institutes of Health Research (CIHR)Principal Investigator
N/A
Research Location
CanadaLead Research Institution
University of British ColumbiaResearch Priority Alignment
N/A
Research Category
Pathogen: natural history, transmission and diagnostics
Research Subcategory
Diagnostics
Special Interest Tags
Innovation
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
point of care ultrasound (POCUS)] when patients first enter the hospital, by any physician with remote support from POCUS experts. In this study, we will test if adding heart and lung ultrasound images to existing clinical and laboratory tests can improve the accuracy and speed of COVID-19 diagnosis. A total of 16 hospitals across British Columbia and Ontario will participate in this study, and we will analyze this large data set using artificial intelligence (AI). Our team has already developed a platform to share ultrasound data and applied AI to study other heart diseases, so we are ready to rapidly apply this approach to COVID-19. If POCUS is effective it would allow earlier treatment and isolation of positive cases, reducing exposure of frontline health care workers and the public to the virus, improving both patient care and the distribution of health resources like personal protective equipment, intensive care beds and ventilators. Because POCUS-based COVID-19 diagnosis can be performed remotely it could also be applied in long term care facilities and in rural areas.