To develop the world's first digital twins of healthcare educators and trainers in advanced laparoscopic gynaecological surgery, utilising deep machine learning to produce a human-like interface which can lead tutorials and training on an online platform autonomously.

Design:

Using a third generation neural network-based language prediction model a purpose coded artificial intelligence (AI) system was prompted to develop training modules for a AI-powered advanced laparoscopic gynaecological surgery training programme. The avatars for the training modules were custom built, based on the lead trainer's facial features and voice. The AI-powered modules were made part of a larger hybrid training programme with an online / webinar component, alongside live training by the same lead trainers.

Setting:

The bespoke AI-generated training modules were added to an already existing advanced laparoscopic training programme for Consultants and Residents in Gynaecology.

Patients or Participants:

10 Consultants and Residents in Gynaecology with an interest in laparoscopic surgery were taught by the digital twins of the lead trainers. The subject matter of the training modules was similar but the content was not the same.

Interventions:

N/A

Measurements and Main Results:

Feedback was collected after the training programme with particular interest in the performance of the digital twins. The feedback was overwhelmingly positive. The digital twins have now also been purposed to carry out assessments in the form of multiple choice questions and collect trainee feedback with subjective responses.

Conclusion:

For a fraction of the true cost of healthcare education, digital twins can enable remote learning, in multiple languages, allowing educators and trainers to reach a wider audience of students without the need for physical classroom space. This can be particularly important in healthcare education, where access to specialized training can be limited in certain geographic regions, not to mention the advantage of objectively tracking and analyzing every nuance of learning performance in the realm of advanced laparoscopic skills.