Description

This new blended learning programme combining opportunities for peer-to-peer interaction with online self-paced e-learning material for a seamless and complementary flow of learning.

This course is for radiologists and allied healthcare professionals in radiology at any level of training or experience, who want to gain a global overview of Artificial Intelligence (AI) in radiology and what it means for the speciality.

Participants will receive access to two interactive e-learning modules (approximately taking 2-3 hours each to complete), as well as a workshop featuring AI experts in the field of radiology. This will help enhance your learning experience and allow you to network with colleagues who share an interest in AI in Radiology.

Learning outcomes

You will be introduced to AI in radiology and healthcare and the fundamental concepts when creating an AI algorithm. By the end, you will:

  1. Gain an understanding of the fundamental principles that form the basis of AI
  2. Be able to describe various AI techniques and their advantages and disadvantages, as well as justify the use of these methods
  3. Acquire basic knowledge of how AI models are created, with a particular focus on data gathering, annotation, and the importance of data management and security
  4. Understand the challenges associated with open-source datasets, be aware of AI grand challenges such as Kaggle, and understand how bias and unintended outcomes can potentially affect AI models.

Course details

  • Launch of e-learning resource: Wednesday 15 November 2023
  • Online workshop: Thursday 18 January 2024 from 9:30 to 15:30 on Zoom

View the programme and register online.

Pre-requisites for attending the workshop

  • Completion of both online e-learning modules one and two before attending the workshop.
  • A laptop available (access for online workshop hosted on Zoom)
  • A Google account for running and accessing the Google Colab practical session

Knowledge from the modules will be assumed in the workshop – delegates will not maximise the learning opportunity from this workshop without having completed the two online modules beforehand.