Intro to AI in Medicine: Practical Issues for Healthcare Professionals - an accredited short course
This weekend mini-course will give healthcare professionals hands-on experience with AI tools for everyday clinical practice.
The Temerty Centre for Artificial Intelligence Research and Education in Medicine (T-CAIREM)'s accredited 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.
Cost: $1,073.50
Learning Objectives
By the end of the course, you will be able to understand and evaluate an AI technology for incorporation into your 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.
Schedule (online)
Day 1 - Saturday, July 25
Morning session, 10am to 12pm EDT
- 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 EDT
Afternoon session, 1pm to 3pm EDT
- 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, model training metrics.
- Q&A group discussion with peers and the instructor.
Day 2 - Sunday, July 26
Morning session, 10am to 12 pm EDT
- 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 EDT
Afternoon session, 1pm to 3pm EDT
- 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.
- 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.
About the instructor: Dr. Nihal Haque
T-CAIREM Education Faculty Affiliate, Temerty Faculty of Medicine
Dr. 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 innovation, Dr. Haque also leads AI-driven research in other areas, including dementia care and medical education in Geriatric Medicine. He is also actively involved with the TCAIREM education committee as a faculty advisor on AI in medical education.
Registration
Contact
Dominic Ali
647-378-6425