most citedCurrent validation practice undermines surgical AI development

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

ExpOS: Explainable Open-Surgery Skills Assessment Using 3D Hand Reconstruction

Roi Papo, Idan Smoller, Shlomi Laufer

Timely and transparent feedback is essential for effective surgical training, yet current assessment remains dependent on expert observation, limiting scalability and opportunities…

cs.CV2026

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…

q-bio.OT20261 cited

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…

cs.CV2026

Monocular pose estimation of articulated open surgery tools -- in the wild

Robert Spektor, Tom Friedman, Itay Or +2

This work presents a framework for monocular 6D pose estimation of surgical instruments in open surgery, addressing challenges such as object articulations, specularity, occlusions…

cs.CV2025

RoHan: Robust Hand Detection in Operation Room

Roi Papo, Sapir Gershov, Tom Friedman +3

Hand-specific localization has garnered significant interest within the computer vision community. Although there are numerous datasets with hand annotations from various angles an…