collaborators

6 papers

q-bio.OT2026

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

Generalized Recognition of Basic Surgical Actions Enables Skill Assessment and Vision-Language-Model-based Surgical Planning

Mengya Xu, Daiyun Shen, Jie Zhang +19

Artificial intelligence, imaging, and large language models have the potential to transform surgical practice, training, and automation. Understanding and modeling of basic surgica…

cs.CV2026

Surg-R1: A Hierarchical Reasoning Foundation Model for Scalable and Interpretable Surgical Decision Support with Multi-Center Clinical Validation

Jian Jiang, Chenxi Lin, Yiming Gu +24

Surgical scene understanding demands not only accurate predictions but also interpretable reasoning that surgeons can verify against clinical expertise. However, existing surgical…

cs.RO2026

Cosmos-H-Surgical: Learning Surgical Robot Policies from Videos via World Modeling

Yufan He, Pengfei Guo, Mengya Xu +11

Data scarcity remains a fundamental barrier to achieving fully autonomous surgical robots. While large scale vision language action (VLA) models have shown impressive generalizatio…

cs.CV2026

SurGo-R1: Benchmarking and Modeling Contextual Reasoning for Operative Zone in Surgical Video

Guanyi Qin, Xiaozhen Wang, Zhu Zhuo +7

Minimally invasive surgery has dramatically improved patient operative outcomes, yet identifying safe operative zones remains challenging in critical phases, requiring surgeons to…

cs.CV2025

Large-scale Self-supervised Video Foundation Model for Intelligent Surgery

Shu Yang, Fengtao Zhou, Leon Mayer +16

Computer-Assisted Intervention (CAI) has the potential to revolutionize modern surgery, with surgical scene understanding serving as a critical component in supporting decision-mak…