4 papers
Looking Beyond the Scale: Do Surgical Skill Models Learn Transferable Representations Across Assessment Rubrics?
Hanna Hoffmann, Felix von Bechtolsheim, Stefanie Speidel +1
Vision-based surgical skill assessment has shown strong in-domain results, yet a fundamental question remains unasked: do these models learn transferable representations of surgica…
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…