FCI Early Careers Group (ECG)
The number of clinicians starting out a career in clinical informatics is increasing and the routes into the specialty are extremely varied. This group aims to represent and support people on their first steps into clinical informatics. If you are at an early point in your clinical informatics career and want to join the group, then we will welcome you with open arms - regardless of your clinical experience or background. Register your interest below.
Previous recordings of group session
How to become a clinical informatician
This webinar, hosted by the FCI Early Careers Group, focused on the different routes to becoming a clinical informatician. The panel was made up of current FCI members from a range of professional backgrounds, discussing how they got into clinical informatics, what their role is like, how this compared to their expectations going in, and tips for those looking to develop their career in clinical informatics.
The Chair and presenters of the webinar are responsible for the content and views expressed in the webinar.
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.