T-CAIREM's Introduction to AI in Medicine: Practical Issues & Recommendations for Healthcare Professionals (July 25-26)
T-CAIREM's upcoming Introduction to AI in Medicine: Practical Issues & Recommendations for Healthcare Professionalsweekend 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, July 25 and July 26, 2026 FORMAT: Virtual (Zoom link will be provided to registered participants) COST: CAD $950 + tax (CA$1,073.50 total)
NOTE: A certificate of course completion and accreditation documentation will be provided for participants who complete the final quiz.
REGISTRATION DEADLINE:July 19, 2026 @ 11:30pm ET
About the Instructor
Dr. Nihal Haque, MD FRCPC
Physician and Hospitalist, North York General Hospital
Dr. Nihal Haque is a physician specializing in geriatric medicine at North York General Hospital in Toronto, Canada, and an Adjunct Assistant Professor at the University of Toronto. 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 a physician representative on his hospital's AI working group and is part of an interdisciplinary team that recently received federal funding from Canada Health Infoway to develop AI solutions to reduce healthcare worker burnout. With a focus on improving patient outcomes through healthcare innovations, Dr. Haque also leads AI-driven research in other areas, such as improving dementia care and enhancing medical education in Geriatric Medicine. He is also actively involved with the TCAIREM education committee as a faculty advisor on AI in medical education.
Schedule
Day 1 (July 25): 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 (July 25): 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 (July 26): 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 (July 26): 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
By the end of the course, the learner 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.
