CAR launches AI training curriculum

OTTAWA – The Canadian Association of Radiologists has created an online education and training course designed to provide radiologists and radiology trainees with an enhanced understanding of artificial intelligence in radiology.

Called “Artificial Intelligence in Radiology: Foundations to Current Applications,” the course is said to be the first and only curriculum of its kind to encompass the practical, technical, and ethical issues of AI integration into radiology from a Canadian perspective.

Completing courses from this accredited curriculum will count toward one’s Royal College MOC requirements.

This curriculum is designed as a primer for radiology trainees as well as practicing radiologists with an interest in the integration of AI and radiology. The aim is also to encourage the use and adoption of this curriculum by program directors of radiology departments. Please note that this curriculum is exclusively available on the CAR’s online learning management platform, RAD Academy, for CAR members and is not publicly accessible.

The initiative was championed by the CAR Artificial Intelligence (AI) Standing Committee.

“Recognizing recent advances in computer vision, we illustrate tasks that are most likely to be automated and the anticipated impact on the work of radiologists. In a nutshell, we present a roadmap to the future of radiology,” said Dr. An Tang (pictured), chair of the AI Standing committee.

This curriculum is designed as a primer for radiology residents and other clinical trainees, as well as practicing medical professionals and researchers with an interest in the integration of AI and radiology. The aim is also to encourage the use and adoption of this curriculum by program directors of radiology departments.

Why do we need a national curriculum for AI in radiology? Commercial AI applications have the potential to significantly impact the quality, reliability, and efficiency of medical imaging, from requisition to image interpretation, and reporting.

Today’s radiologists and future practitioners need to be prepared for the adoption of such products into their clinical workflow. This requires that they have the fundamental knowledge to grasp the inner workings of these systems.

The curriculum will provide professionals with the technical literacy necessary to communicate with data scientists and software developers, guide the direction of research to harness the most useful outcomes, and voice informed criticism when developments become decoupled from improved patient care.

CAR designed this interactive curriculum to help healthcare professionals to better understand the importance and effectiveness of AI in radiology, and to familiarize themselves with fundamental concepts of machine learning and deep learning neural networks.

Drawing on the expertise of researchers and clinicians from across the country, CAR developed activities which delve into topics ranging from the fundamentals of AI to the research landscape and ethical aspects of AI in radiology. The curriculum presents another opportunity for CAR members to earn Section 3 Self-Assessment Program credits.

How is this curriculum structured?

CAR divided the introductory curriculum into five courses. The format of these modules will vary depending on the content, and may deploy a variety of educational methodologies, such as guided readings, quizzes, reflections, videos, and interactive eLearning activities. For more information, see car.ca