Course Outline

Prof Albert Bifet – Artificial Intelligence Institute, University of Waikato

Prof David McCormack – Division of Health, University of Waikato

0845: Coffee and Registration

0900 - 1000: Introduction to AI
Overview of AI concepts and their relevance to healthcare.

1000 - 1100: Data in AI
Exploring the role of data in AI applications.

1100 - 1200: Practical Session: Building a Classifier
Hands-on activity using Google's Teachable Machine.

1200 - 1300: Lunch

1300 - 1400: Deep Learning and Computer Vision
Applications of deep learning in healthcare diagnostics.

1400 - 1500: Automation and AI Integration
Implementing AI to enhance healthcare workflows.

1500 - 1600: Practical Session: Data Science
Engage with data science tools and techniques.

1600: End of Day 1

0845: Coffee and Registration

0900 - 1000: AI Ethics in Healthcare
Covering ethical and legal considerations.

1000 - 1100: Explainable AI
Ensuring transparency and fairness in AI decisions.

1100 - 1200: Practical Session: Explainable AI Tools
Hands-on with WebSHAP for model interpretation.

1200 - 1300: Lunch

1300 - 1400: Advanced AI Applications and Regulatory Considerations
Discussion led by industry experts.

1400 - 1500: AI & Health Research
Case studies and practical examples of AI in healthcare research.

1500 - 1600: Practical Session: Designing Research Protocols
Collaborative session to develop AI-integrated research protocols.

1600: End of Course