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AI in Healthcare has the potential to transform care delivery, teaching, and learning across all health care professions. Today, the hype for AI has far exceeded the science on AI implementation and education. Join us at this journal club to learn more about the advances and challenges to safely deploy AI in health care.
Wednesday, May 5, 2021 12:00 pm – 1:00 pm
RSVP for this meeting:Zoom Meeting
After registering, you will receive a confirmation email containing information about joining the meeting.
Hatherley, J. J. (2020). Limits of trust in medical AI. Journal of Medical Ethics, 46(7), 478-481. https://jme.bmj.com/content/46/7/478
Ferrario, A., Loi, M., & Viganò, E. (2020). Trust does not need to be human: it is possible to trust medical AI. Journal of Medical Ethics. https://jme.bmj.com/content/early/2020/11/25/medethics-2020-106922
Dr. Daniel Buchman is a Bioethicist and Independent Scientist in the Campbell Family Mental Health Research Institute at CAMH. He is also an Assistant Professor in the Dalla Lana School of Public Health at the University of Toronto, a member of the University of Toronto Joint Centre for Bioethics, and an Affiliate Scientist in the Krembil Research Institute at the University Health Network. Dr. Buchman’s program of research explores ethical issues at the intersection of clinical practice and public health. His primary areas of research interest include ethical issues related to mental health, substance use, and chronic pain. Themes related to stigma, identity, moral responsibility, and compassion feature prominently in his work, and he has a longstanding teaching interest in empirical approaches to bioethics. Some of Dr. Buchman’s current research interests are in the areas of ethics of artificial intelligence and machine learning in mental health, neuroethics, and psychedelic-assisted mental health care.
Globe and Mail reading:
How can we keep algorithmic racism out of Canadian health care’s AI toolkit?(You may register for a free article).
LLana James. is the AI, Medicine and Data JusticePost-Doctoral Fellow at Queen's University. She is also wrapping up her doctoral studies at the University of Toronto, Faculty of Medicine. Her research is focused on the intersection of AI applications in, clinical care, population health, public health data science and the law, and its particular implications for BlackLife. LLana’s recent thinking and research can be found in the
Globe and Mail,
The Conversation, the
Toronto Star, the
AI Health podcast and the web series
COVID Conversations, which is the first and longest running pan-Canadian series on racebased data collection, AI, Big Data, privacy, ethics and equity in health. You can find more at
@REDE4BlackLives on Twitter.
McCoy, L. G., Nagaraj, S., Morgado, F., Harish, V., Das, S., & Celi, L. A. (2020). What do medical students actually need to know about artificial intelligence?
NPJ Digital Medicine, 3(1), 1-3.
Dr. Sunit Das is a neurosurgeon and scientist at St. Michael’s Hospital and the Research Institute of the Hospital for Sick Kids and an Associate Professor in the Department of Surgery at the University of Toronto. Dr. Das work has been published in many high impact journals, including
Cell Stem Cell,
JAMA Neurology, and the
New England Journal of Medicine. In 2017, he joined the Centre for Ethics at the University of Toronto. His work at the Centre for Ethics focuses on the interface of AI with medicine, and issues that underlie professional identify in medical practice.
Gratzer, D., & Goldbloom, D. (2020). Therapy and E-therapy—Preparing Future Psychiatrists in the Era of Apps and Chatbots.
Academic Psychiatry, 1-4.
Dr. David Gratzer is a psychiatrist at CAMH. He is the co-chief of the General Adult and Health Systems Division for inpatient care and practice innovation. He has published and presented nationally and internationally on digital psychiatry and serves on the editorial board of
JMIR Mental Health and is an associate editor (social media and digital psychiatry) of
The Canadian Journal of Psychiatry.
Wiljer, D., & Hakim, Z. (2019). Developing an Artificial Intelligence–Enabled Health Care Practice: Rewiring Health Care Professions for Better Care.
Journal of Medical Imaging and Radiation Sciences, 50(4), S8-S14.
https://www.sciencedirect.com/science/article/pii/S1939865419305430Kemp J, Zhang T, Inglis F, Wiljer D, Sockalingam S, Crawford A, Lo B, Charow R, Munnery M, Singh Takhar S, Strudwick G. Delivery of compassionate mental health care in a digital technology-driven age: A scoping review.
J Med Internet Res. DOI: 10.2196/16263 URL:
Dr. David Wiljer is the Executive Director of Education, Technology & Innovation at the University Health Network, and an Associate Professor in the Department of Psychiatry, Faculty of Medicine and the Institute of Health Policy Management and Evaluation at the University of Toronto.
His work focuses on patient and health professions education, digitally enabled education and life-long learning. He has explored the development of large programs, infrastructure, communities, and research initiatives that involve health professionals, patients and families in new approaches to education and care delivery.
Dr. Wiljer's session focused on how health care professionals and organizations can build capacity and capabilities to safely deploy AI in Healthcare.
One of the greatest priorities facing health care professionals today is the integration of AI into healthcare provision. Research demonstrates that AI has the potential to transform clinical practice and teaching and learning across the health care professions. And while the perils and challenges associated with AI are often underscored in the literature, our understanding of the strategies to harness those perils and mitigate AI risks is evolving.
The Institute for Education Research (TIER) and the Wilson Centre at University Health Network (UHN) are pleased to announce the launch of a dedicated Journal Club on “AI in Healthcare Education”, hoping to create a dynamic space for all who are interested in engaging with scholarship on the impact of AI healthcare and education.
Jha and Topol’s 2016
Adapting to Artificial Intelligence: Radiologists and pathologists as information specialists.The 2018
Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology (page 120 – beginning of 125 only)
A radiation therapist by training,
Caitlin Gillan, MRT(T), BSc, MEd, FCAMRT is the Manager of Education and Practice for Toronto’s Joint Department of Medical Imaging between the University Health Network (UHN), Sinai Health System, and Women’s College Hospital, as well as for UHN’s Laboratory Medicine Program. She graduated in 2007 from the Medical Radiation Sciences Program offered jointly between the Michener Institute and the University of Toronto (UofT), and subsequently completed her MEd in Health Professional Education at the Ontario Institute of Studies in Education in 2009. She is an Assistant Professor in the UofT Department of Radiation Oncology, with research interests in interprofessional education and practice, especially as they relate to the integration of novel technologies and practice innovations.
Professionally, Caitlin has served as the Associate Director of Curriculum for the Masters in Health Science, Medical Radiation Sciences Program at UofT. She has also maintained a high level of engagement with the Canadian Association of Medical Radiation Technologists, serving a three-year term on their Board of Directors from 2009 – 2011, and currently helping to lead the ramping up of their Advanced Practice Registered Technologist (APRT) certification process. She is working now to complete her doctoral studies through UofT’s Institute of Health Policy, Management, and Evaluation, focusing on how healthcare professions are preparing for future practice in light of artificial intelligence.