About the project

An endoscopy is a medical procedure used for the detection, diagnosis, and treatment of various internal conditions. However, learning to perform endoscopic procedures and conducting accurate assessments requires extensive training and expertise. In collaboration with UZ Ghent, this project aims to enhance endoscopic training and improve the accuracy of endoscopic procedures by leveraging computer vision algorithms and artificial intelligence (AI).

IDLab role

IDLab has the following tasks during the project:

• Develop objective skill assessment methods: Research and design methodologies to automatically and objectively evaluate the skill level of trainees performing endoscopic procedures on non-human examples. This approach aims to enhance the accuracy of trainee assessments, enabling tailored feedback and optimizing their training trajectory for improved learning outcomes.
• Create AI models for diagnostic support: Design and implement artificial intelligence models capable of identifying a wide range of conditions during live endoscopic procedures. These models will serve as decision-support tools for endoscopists, ensuring more accurate diagnostics and facilitating better clinical decision-making.