AI in Health Certificate
Helping You Make AI Happen in Healthcare
March 6, March 13, March 27, and April 3, 2020
Location: Institute of Health Policy, Management and Evaluation
155 College Street, Toronto ON
Time: 8:30 AM – 5:00 PM
- $1750 + hst early bird pricing
- $1950 + hst regular pricing
As a flagship component of an overarching Artificial Intelligence in the Health Sector initiative being championed at the Institute of Health Policy Management and Evaluation, the inaugural Artificial Intelligence in Health Certificate will launch in March 2020, with registration opening in December 2019.
This four day certificate program will prepare learners to apply innovations in AI for health. Learners will gain an understanding of the fundamental concepts of AI, current applications and emerging trends of AI for health, and a practical understanding of how to implement AI for health in their own organizations through a case project.
Who Should Attend?:
This program is applicable for health care providers, health administrators, health informatics professionals, and others across the health sectors (e.g. evaluators, researchers, etc.).
**Note** Learners should have at least 2 years of experience working in the health sector.
At the completion of this certificate program, learners will be able to:
- Define and apply fundamental concepts of AI, and describe current applications and emerging trends of AI for health
- Apply AI in health within their own organization through their case project
- Identify and assess opportunities, barriers, and limitations of AI in health and healthcare
- Apply relevant perspectives on the implementation of AI in health (ethics, policy, strategy, business, governance)
- Critically assess various business cases appropriate for AI initiatives within the healthcare context
- Assess the landscape of available data and governance of the data.
- Apply concepts of confidentiality, privacy, and security to health AI applications
- Utilize concepts related to Machine Learning, and how they can be applied to health and healthcare
Format of Program
Minimum 39 hours for a Certificate of Completion, the College of Family Physicians of Canada Main Pro + credits, and Royal College of Physicians and Surgeons Section 1 accreditation with Faculty of Medicine CPD:
- Virtual orientation: not part of hours counted
- At home pre-course work: define individual case study and submit: 1 hour
- At home pre-reading for each module: 0.5 hours X 7 modules: 3.5 hours
- 8 content modules (each module is 3.5 hours in class) = 28 hours
- At home post- work: 1 hour of reflection questions X 6 modules (7th module will occur during last day) : 6 hours
- Presentation preparation on individual case= 2 hours
Total: 40.5 Hours
College of Family Physicians of Canada – Mainpro+:
This one-credit-per-hour Group Learning program meets the certification criteria of the College of Family Physicians of Canada and has been certified by Continuing Professional Development, Faculty of Medicine, University of Toronto for up to 28.0 Mainpro+ credits.
Royal College of Physicians and Surgeons of Canada – Section 1
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, approved by Continuing Professional Development, Faculty of Medicine, University of Toronto. You may claim a maximum of 28 hours.
Canadian College of Health Leaders – Maintenance of Certification
MAINTENANCE OF CERTIFICATION
Attendance at this program entitles certified Canadian College of Health Leaders members (CHE / Fellow) to 10 Category II credits towards their maintenance of certification requirement.
March 6, 2020
Module 1: Fundamentals of AI – Laura Rosella
Module 2: AI Applications in Healthcare – Bo Wang
March 13, 2020
Module 3: Ethics and Policy of AI for Health – Jay Shaw & Sally Bean
Module 4: Health AI Strategies and Business Cases- – Zaki Hakim & Michael Caesar
March 27, 2020
Module 5: Data and Information Governance – Eric Sutherland
Module 6: AI Implementation & Adoption – Zaki Hakim & Michael Caesar
April 3, 2020
Module 7: Practical Guide to Machine Learning – Ali Vahit Esensoy & Elham Dolatabadi
Module 8: Learner presentations (syllabus not provided)- Emily Seto & Julia Zarb (facilitators)