Workshop: 1.00pm - 4.00pm.
Afternoon tea is provided.
In this interactive workshop Albert and David will:
- Overview AI concepts and a brief history and current state of AI in healthcare.
- Explore the role of data in AI applications and the types of data used in healthcare AI.
- Practical Session: Building a Simple Classifier: Hands-on activity using Google's Teachable Machine with a focus on understanding how AI learns from data.
- Provide an introduction to deep learning concepts and applications in medical imaging and diagnostics.
- Overview how AI can enhance healthcare workflows with a discussion on potential implementation in primary care settings.
- Brief hands-on experience with basic data analysis: Understanding how AI interprets healthcare data.
- Provide an introduction to the concept of explainable AI and the importance of transparency in AI-assisted decisions for GPs
There will be time at the end for an open discussion on AI's role in general practice.
Cost
- Registration fee per session (add-on to Goodfellow Symposium registration) - $345
- Registration fee per session, Friday only participants (not part of Goodfellow Symposium) - $365
This workshop has been endorsed and approved for professional development by The Royal New Zealand College of General Practitioners (2.5 hrs, 5 points), and the College of Nurses Aotearoa NZ for 2.5 professional development hours.
Presenter
David McCormack
David is a cardiothoracic surgeon and healthcare leader, currently serving in the National Clinical Senior Leadership Team Health New Zealand - Te Whatu Ora. David is the National Clinical Lead for Health Technology Management. He maintains an active clinical practice alongside his leadership roles.
As a fellow of several international surgical colleges and part of the New Zealand Jurisdictional Committee for the Royal Australasian College of Medical Administrators, David combines clinical experience with insights into healthcare administration. His interest in artificial intelligence and its applications in healthcare has led to his role as the AI Health Lead for the AI Institute and as a member of the National AI and Algorithm Expert Advisory Group for Health New Zealand - Te Whatu Ora.
David collaborates with the Artificial Intelligence Institute at the University of Waikato and is part of the New Zealand Artificial Intelligence Researchers Association. Recognizing the importance of AI education in healthcare, he co-founded the "Introduction to AI for Healthcare Professionals" course at the University of Waikato and the popular “Waikato AI Research and Interest Group’.
Motivated by a desire to enhance patient care, David works towards advancing healthcare through the integration of clinical practice and technological innovations, particularly exploring the potential of AI in improving healthcare systems.
David currently serves in the Division of Health at the University of Waikato, where he continues to contribute to research and education in healthcare and AI.
Presenter
Albert Bifet
Albert is a Professor of AI, Director of the Te Ipu o te Mahara AI Institute at the University of Waikato and Co-chair of the Artificial Intelligence Researchers Association (AIRA). His research focuses on Artificial Intelligence, Big Data Science, and Machine Learning for Data Streams.
He is leading the TAIAO Environmental Data Science project and co-leading the open source project MOA Massive On-line Analysis.
He is the co-author of a book on Machine Learning from Data Streams published at MIT Press. He is one of the winners of the best paper award at the ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) 2023, and he is the general co-chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2024
