Reflect the Emerging Role of Artificial Intelligence

Groundbreaking Imagination

Groundbreaking Imagination

Build capacity to reflect the emerging role of artificial intelligence in health professions.

Building training opportunities around AI will raise awareness and reduce stress and anxiety about the use of AI in clinical care.

Technology is at the heart of advancing this goal. In developing strategic partnerships that will advance this goal, we will ensure clear policies are in place for material transfer agreements as well as data ownership, management and security.

2019 Dean's Report Highlights: The working group is proposing a new centre for machine learning medicine, which will help coordinate research in the field and develop curriculum and learning modules for learners, faculty and practising health professionals. An inaugural symposium on machine learning in medicine will run on November 21 – the first of many more learning opportunities on artificial intelligence and machine learning for members of our community. 

The Team

Decanal Sponsor: Trevor Young

Co-Chairs: Rita Kandel & Kaveh Shojania

Working Group Members:

  • Alan Moody, Professor and Chair, Medical Imaging 
  • Rita Kandel, Professor and Chair, Laboratory Medicine and Pathobiology
  • Marcus Law, Associate Professor and Director of Foundations, MD Program
  • Kaveh Shojania, Professor and Vice-Chair, Quality & Innovation, Department of Medicine
  • Suzan Schneeweiss, Professor and Associate Dean, CPD, Post MD Education
  • Bo Wang, Assistant Professor and Lead Artificial Intelligence Scientist, Peter Munk Cardiac Centre and the Techna Institute at the University Health Network 

Staff Support: Liam Mitchell, Office of Communications; Brien Wong, CPD Team

2019 Dean's Report Update

A. The working group has accomplished the following to date:

  • Conducted a review of activities underway in Toronto related to the application of Artificial Intelligence and machine learning in medicine;
  • Reviewed current educational offerings in Artificial Intelligence and machine learning;
  • Organized a half-day symposium on machine learning in medicine, to be offered in November 2019; and,
  • Consulted broadly in preparing a proposal to establish an Extra-Departmental Unit (Type C) that will help coordinate research in the field and develop curriculum and learning modules for learners, faculty and practising health professionals. 

B. Over the next year, the working group aims to accomplish the following:

  • Launch a new centre for research and education in machine learning in medicine; and,
  • Expand educational offerings related to machine learning in medicine, with an emphasis on learning modules for learners and current healthcare professionals.