5 papers
Artificial Intelligence for Workflow Analysis in Colorectal Surgery: A Multicentric, Cross-Procedural Development and Generalization Study
Pietro Mascagni, Julia Alekseenko, Pooja P Jain +10
Minimally invasive colorectal surgeries (MIS-CRS) are characterised by significant variability and inconsistent outcomes. ColoWorkflow, a tool for the video-based assessment (VBA)…
SPIRIT: Spatio-temporal Pairwise Relational Modeling of Instrument-Tissue Interactions for Surgical Action Triplet Recognition
Saurav Sharma, Lorenzo Arboit, Nabani Banik +11
Fine-grained understanding of surgical activity is essential for context-aware assistance in the operating room, including safety monitoring, adverse event identification, and skil…
GEN-Guard: Correcting Generalization Failures for Deployable Federated Surgical AI
Julia Alekseenko, Pietro Mascagni, AI4SafeChole Consortium +1
Federated Learning (FL) in surgical video AI enables collaborative model training without sharing sensitive data. However, standard evaluation practices - selecting the "best" glob…
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…
Clinnova Federated Learning Proof of Concept: Key Takeaways from a Cross-border Collaboration
Julia Alekseenko, Bram Stieltjes, Michael Bach +4
Clinnova, a collaborative initiative involving France, Germany, Switzerland, and Luxembourg, is dedicated to unlocking the power of precision medicine through data federation, stan…