4 papers
OSS: Open Suturing Skills Vision-Based Assessment Challenge 2024-2025
Hanna Hoffmann, Setareh Bady, Claas de Boer +54
Achieving high levels of surgical skill through effective training is essential for optimal patient outcomes. Automated, data-driven skill assessment holds significant potential to…
Current validation practice undermines surgical AI development
Annika Reinke, Ziying O. Li, Minu D. Tizabi +97
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contr…
Federated Learning for Surgical Vision in Appendicitis Classification: Results of the FedSurg EndoVis 2024 Challenge
Max Kirchner, Hanna Hoffmann, Alexander C. Jenke +16
Developing generalizable surgical AI requires multi-institutional data, yet privacy constraints preclude direct data sharing, making Federated Learning (FL) a natural candidate. It…
Federated EndoViT: Pretraining Vision Transformers via Federated Learning on Endoscopic Image Collections
Max Kirchner, Alexander C. Jenke, Sebastian Bodenstedt +5
Purpose: Data privacy regulations hinder the creation of generalizable foundation models (FMs) for surgery by preventing multi-institutional data aggregation. This study investigat…