overview

The AI in Health Readiness Forum is a highly specialised event designed to explore the important considerations around AI adoption in healthcare and weigh the readiness in different contexts and clinical settings.

We already have AI being used within healthcare, but how ready are our health systems?

Through a case study and discussion-led agenda, this one-day summit will explore the importance of getting some of the basics right and understanding the “tools in the kit” before embarking on your journey with AI.

Bringing together key stakeholders involved in the safe and responsible use of AI in the field: Clinicians, CMOs, Digital Health Leaders, Clinical Governance Leaders, and Health Service Leaders. Medical and Clinical Directors, Directors of Patient Safety, Innovation Managers, CEOs, CIOs, Chief Innovation Officers, Chief Digital Officers, Federal & State government departments and agencies, Tech and Pharma companies, as well as Allied health.

This 1 Day event will explore the readiness of the workforce, health services, and workflows. What are the applications for AI in health which are ready? How is it being used effectively and what have been the learnings which can be translated across other areas of health and medicine?

Topics to be addressed:

• Real-life application of AI within Clinical Settings
• Good clinical governance: why this is critical when deploying an AI algorithm?
• The regulatory approach to AI
• Who’s to blame when it goes wrong? Assisted decision making
• Prepping your roadmap: get the basics built to eventually support AI
• How do you ensure you have the right tools in your “kit”?
• Skills and workforce considerations for AI readiness: developing in-house capabilities
• Safe and Responsible Use of AI in Health
• Case Studies
• Ensuring the data is fit for purpose & the importance of clean data to feed into the AI
• Decision support and how you measure and calculate
• Privacy and data protection
• Best use cases and where is it not the right tool for the job?
• Standards of practice in relation to deployment – where is the evidence at scale?
• Overcoming the challenge of implementing and scaling the use of AI
• Learnings from successes, challenges, and learnings from failures, future directions