Challenges in multi-centric generalization: phase and step recognition in Roux-en-Y gastric bypass surgery.
Joël L LavanchySanat RameshDiego Dall'AlbaCristians GonzalezPaolo FioriniBeat P Müller-StichPhilipp C NettJacques MarescauxDidier MutterNicolas PadoyPublished in: International journal of computer assisted radiology and surgery (2024)
MultiBypass140 shows considerable variation in surgical technique and workflow of LRYGB procedures between centers. Therefore, generalization experiments demonstrate a remarkable difference in model performance. These results highlight the importance of multi-centric datasets for AI model generalization to account for variance in surgical technique and workflows. The dataset and code are publicly available at https://github.com/CAMMA-public/MultiBypass140.