CRISTAL: Adapting Workplace Training to the Real World Context with an Intelligent Simulator for Radiology Trainees

Hope Lee, Amali Weerasinghe, Jayden Barnes, Luke Oakden-Rayner, William Gale, Gustavo Carneiro

Intelligent learning environments based on interactions within the digital world are increasingly popular as they provide mechanisms for interactive and adaptive learning, but learners find it difficult to transfer this to real world tasks. We present the initial development stages of CRISTAL, an intelligent simulator targeted at trainee radiologists which enhances the learning experience by enabling the virtual environment to adapt according to their real world experiences. Our system design has been influenced by feedback from trainees, and allows them to practice their reporting skills by writing freeform reports in natural language. This has the potential to be expanded to other areas such as short-form journalism and legal document drafting.

The final publication is available at Springer via