The CAR is working with Amazon Web Services (AWS) to drive artificial intelligence and machine learning adoption across Canadian healthcare
AWS is the world’s most comprehensive and broadly adopted cloud platform. It has more than 200 services including a deep bench in the area of artificial intelligence. The CAR’s collaboration with AWS is to help advance the intersection of technology and healthcare delivery for radiologists through education and access to industry leading cloud services.
“Radiology is moving at a rapid pace. Innovation and new technologies allow for improved patient care, ultimately improving health outcomes for Canadians,” said Dr. Michael Barry, President, CAR. “We believe that cloud-based imaging is the future of medical imaging, and we are excited to be moving forward with this agenda in concert with AWS.”
AWS has already been involved with the medical imaging community in Canada. Most notably, through an open-source project at the University of British Columbia Cloud Innovation Centre (UBC CIC). The Open-Source AI Model for COVID-19 CT Diagnostics and Prognosis has garnered international attention. Working with radiologists at Vancouver General Hospital (VGH), and University of British Columbia’s (UBC) Department of Radiology, the UBC CIC built an AI model to predict the likelihood of COVID-19 based on CT scans and Chest X-rays. Teams collected and coded CT and X-ray data from around the globe, including scans from the Middle East, Italy, South Korea, and of course Canada. It’s the world’s largest COVID CT and X-ray data set, and radiologists and clinicians around the world can use the model today.
This is just one example of the power of artificial intelligence and cloud computing that are advancing our field of study. AWS provides healthcare organizations with the broadest and deepest set of machine learning services in the cloud: from pre-trained AI services for computer vision, language, recommendations, and forecasting; to services to quickly build, train and deploy machine learning models at scale; to custom models with support for popular open-source frameworks.
Another recent example, also from the UBC CIC, is a project called “CAN’T-WAIT” from Vancouver Coastal Health for the lower Mainland MRI Central Intake Office (CIO). It uses machine learning and natural language processing to interpret the fields of MRI requisitions and predict their priority based on CAR wait time guidelines. This proof of concept is being refined for clinical use, but also shows promise for triaging CT scans, ultrasounds, and other medical procedures where formal prioritization guidelines from the medical community exist.
“Diagnostic imaging has always been a technological leader in the health system, and the CAR continues that tradition with its focus on artificial intelligence, machine learning, and other innovative technologies that can bring improvements to the delivery of care” said Larry Sylvestre, AWS Canada’s Healthcare Lead. “We are honored to collaborate with the CAR as they continue their leadership in these areas, and we look forward to supporting their membership to stay at the leading edge of technology in healthcare.”
AWS will be participating in the CAR’s Annual Scientific Meeting taking place digitally from April 27 to May 2. For more information visit their ambassadors in the virtual exhibit hall or website.