T-CAIREM's Intro to AI in Medicine: Practical Issues & Recommendations for Healthcare Professionals (Deadline: Oct. 8)
T-CAIREM's Introduction to AI in Medicine: Practical Issues & Recommendations for Healthcare Professionals weekend mini-course offers practical, hands-on exposure to the tools, opportunities, and implications of AI in your practice. You’ll leave with strategies to improve productivity and insights into the role AI is playing in your specialty. No coding experience is required. This is not a course designed to develop an AI tool. Instead, it focuses on current practical applications of AI in healthcare and their clinical implications.
COURSE TIMES & DATES: 10am to 3pm ET, October 17 & 18, 2026
FORMAT: Virtual (Zoom link will be provided to registered participants)
COST: CAD $950 + tax
REGISTRATION DEADLINE: October 8, 2026 at 11:30pm ET
NOTE: A certificate of course completion and accreditation documentation will be provided for participants who complete the final quiz.
Meet the instructor
Dr. Nihal Haque, MD FRCPC
Chief Medical Information Officer and Geriatrician, Scarborough Health Network
Dr. Nihal Haque is the Chief Medical Information Officer (CMIO) and a practicing geriatrician at Scarborough Health Network. He is also an Assistant Professor at the Temerty Faculty of Medicine. He serves as a faculty affiliate with the T-CAIREM education committee on AI in medical education. He has obtained certification in Artificial Intelligence (AI) in Healthcare from the Michener Institute and Harvard T.H. Chan School of Public Health. He is actively involved in AI‑driven research and innovation, with ongoing projects that include AI applications in delirium care, AI chatbots for medical resident training and AI-assisted discharge summary creation for complex, frail older inpatients. Dr. Haque has also provided strategic guidance to AI start‑ups, advising them on privacy and regulatory pathways, research design, clinical validation and commercialization. He was also part of an interdisciplinary academic team that received federal funding from Canada Health Infoway to develop AI solutions to reduce burnout among healthcare workers. He also teaches about practical applications of AI to healthcare executives through the Rotman School at the University of Toronto. He is currently a fellow in the AMS-Fitzgerald Fellowship in AI & Human-Centred Leadership at the Dalla Lana School of Public Health.
Course Outline
Day 1 (October 17): 10am to 12pm ET
• Introduction to AI (Algorithms, how is AI different from a non-AI computer program, what is machine learning).
• Introduction to generative AI and Large Language Models (LLM): Why are they in the news, and how can they be used practically for day-to-day medical applications?
• Q&A group discussion about practical, real-life examples and scenarios
Lunch Break: 12pm to 1pm ET
Day 1 (October 17): 1pm to 3pm ET
• Discuss the types of AI algorithms to know for medical practice/ terminology needed to understand medical AI.
• Discuss CNN, predictive algorithms, classification algorithms, supervised versus unsupervised learning, and model training metrics.
• Q&A group discussion with peers and the instructor.
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Day 2 (October 18): 10am to 12 pm ET
• Medicolegal session: Medicolegal risks when using AI in practice, including discussion of current CMPA guidelines.
• CPSO/data privacy session: Privacy and professional considerations when using AI in practice, including College of Physicians of Ontario guidelines.
• Q&A group discussion.
Lunch Break: 12pm to 1pm ET
Day 2 (October 18): 1pm to 3pm ET
• Discussion: How do I evaluate an AI product for use in my practice? Approach to implementing AI in your hospital or clinic practice. Will cover data privacy considerations, how to make a proper consent form for AI applications, and which departments to involve in getting an AI product approved for use.
• Answer: How can I incorporate AI into my day-to-day practice - review of examples of applications ready to use now (AI scribes, AI chatbots, AI apps for CME, AI apps for finding medication information).
• Focus on: What resources can I use to stay up to date on medical AI?
• Q&A group discussion.
Learning Objectives
After active engagement in this program, participants will be able to understand and evaluate an AI technology for incorporation into their day-to-day practice through the following learning objectives:
• To describe the fundamental concepts of artificial intelligence, including the distinction between AI and traditional computer programs, and explain the practical applications of generative AI and Large Language Models (LLMs) in clinical practice.
• To identify key AI algorithms relevant to medical practice and how they are used to solve day-to-day clinical problems.
• To analyze the medicolegal and ethical issues associated with AI use in clinical practice, incorporating current CMPA, CPSO, and data privacy guidelines.
• To develop a structured approach to assessing AI tools for clinical use in your clinic or hospital setting, including considerations for data privacy, patient consent, and workflow integration, while identifying readily available AI applications that can enhance day-to-day medical practice.
REGISTRATION DEADLINE: October 8, 2026 at 11:30pm ET
Accreditation
This course has the following accreditation:
College of Family Physicians of Canada (CFPC): This activity has been certified by the College of Family Physicians of Canada for up to 8.0 Mainpro+ Certified Activity credits.
Royal College of Physicians and Surgeons of Canada (RCPSC) – Section 1: 8.0 hours
This event is an Accredited Group Learning Activity (Section 1) as defined by the Maintenance of Certification Program of the Royal College of Physicians and Surgeons of Canada, and approved by Continuing Professional Development, Temerty Faculty of Medicine, University of Toronto. You may claim up to a maximum of 8.0 hours (credits are automatically calculated).
American Medical Association - AMA PRA Category 1 Credit : 8.0 credits
Through an agreement between the Royal College of Physicians and Surgeons of Canada and the American Medical Association, physicians may convert Royal College MOC credits to AMA PRA Category 1 Credits. For more information on the process to convert Royal College MOC credit to AMA credits please see: https://www.ama-assn.org/education/earn-credit-participation-international-activities
European Union for Medical Specialists (UEMS): 8.0 credits
Live educational activities recognized by the Royal College of Physicians and Surgeons of Canada as Accredited Group Learning Activities (Section 1) are deemed by the European Union of Medical Specialists (UEMS) eligible for ECMEC®.
Contact
You can send any questions to t.cairem@utoronto.ca.