FCI Artificial Intelligence Special Interest Group (AI SIG)

   With recent progress on AI and the promise it offers for the transformation of UK healthcare, a SIG has been established to discuss the professional issues raised by AI and how they can be addressed and to share knowledge on effective implementations.

Register your interest below.

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Please see recordings of previous AI SIG sessions below:

An Introduction to Machine Learning and Healthcare AI

On 19th January 2021, the Faculty of Clinical Informatics held an introductory webinar on Machine Learning as a joint session between the FCI Artificial Intelligence and Early Careers Special Interest Groups. The session was presented by Dr Kieran Zucker and Chaired by Professor Jeremy Wyatt.

Artificial intelligence and machine learning technologies have received growing attention over the past decade. The combination of improvements in computer power and refinement of methods have resulted in a number of high profile success stories. There is growing interest in how these approaches can be applied in healthcare delivery, with an ever increasing number of tools being developed over time. Despite plans for wide scale adoption, many working in healthcare know little about machine learning and artificial intelligence. This talk will provide a basic introduction to machine learning and artificial intelligence and give a high level overview of how it works. Using a number of real world examples, focus will be given to not only the potential of machine learning in healthcare, but also some of the many pitfalls that could lead to disastrous consequences.

 
 

The Chair and presenter of the webinar are responsible for the content and views expressed in the webinar.

Download the slides in PDF


AI Special Interest Group Webinar - What is “computable biomedical knowledge”, and why is it important?

Presenter: Prof Jeremy Wyatt DM FRCP, FCI Founding Fellow; emeritus professor of Digital Healthcare, University of Southampton; chair of FCI AI Special Interest Group & former chair, European Society for AI in Medicine.

AI has been around since before the 1956 Dartmouth workshop, and it was already clear then that several different forms of AI would be important, including machine learning of algorithms from data and symbolic representations for use in reasoning.  

This webinar focused on the second of these, symbolic representations or “computable knowledge”. Building on the work of the American Mobilising Computable Biomedical Knowledge (MCBK) activity and a recent MCBK workshop here supported by FCI, we explored:

  1. The evidence that knowledge-based decision support systems improve medical decisions

  2. The definition of computable, as opposed to human readable, knowledge

  3. How such knowledge is already used in a wide range of software tools in healthcare

  4. Current challenges around acquiring computable knowledge

  5. The MCBK vision for how a global library of computable knowledge objects could address some of these challenges

  6. Some technical and other barriers that need to be overcome to realise this vision

This webinar should be of interest to anyone who is concerned about improving clinical decisions and quality improvement in healthcare.

 
 

The Chair of the webinar is responsible for the content and views expressed in the webinar. 

Download the slides in PDF