Liminal^x

This episode marks the end of Series 1 of the LiminalX podcast. The largest conference for medical physicists occurs next week in Vancouver. This episode is dedicated to attendees of the conference and provides an overview of ways to learn about the readiness and adoption of artificial intelligence in the radiation oncology field. http://liminal-x.ai/aapm

Healthcare has always been a team effort and the introduction to AI is no different. In this episode we explore what we can learn from engineers and physicists who maintain the performance of hardware and see what principles we can translate to challenges we currently face in AI.

History tends to repeat itself. In this episode, we'll investigate what lessons from other major technological adoptions like electricity or the Internet we can apply to the adoption of Artificial Intelligence, and establish three personal rules that can help each one of us navigate this technological change in a health care environment.

Most healthcare professionals think they're ready for AI. They're not — and the gap between what they know and how they actually behave when AI is in the room is costing patients. In this episode, Paul Naine draws on two decades of clinical technology adoption to make a case that nobody in healthcare is making clearly enough: AI isn't a product. It's a general-purpose technology. And we've been tr...

After watching a autonomous taxi get stuck in a flood last week, we examine why training data is so important for AI and what three areas we have to be particularly vigilant about when it comes to AI in healthcare. Join us, ask better questions, and comment if you notice something interesting about this episode.

What is the difference between effectiveness and efficacy and how does AI get FDA clearance? Join this to discover how the AI in your clinic got there! 

In this episode we explore the question - "what will it take for me to trust AI in healthcare?" and in doing so introduce a framework that allows us to start building that trust.

If the phrase of the early 2020s was " You're on mute ", the phrase of the late 2020s is shaping up to be " AI content may be inaccurate ". Join us as we open our discussions on why this simple little phrase has profound implications for the application of AI in healthcare.

Welcome to LiminalX! Start here for a short introduction of what LiminalX is, who we are and why we do what we do!