8 papers
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…
Surgical Gaussian Surfels: Highly Accurate Real-time Surgical Scene Rendering using Gaussian Surfels
Idris O. Sunmola, Zhenjun Zhao, Samuel Schmidgall +4
Accurate geometric reconstruction of deformable tissues in monocular endoscopic video remains a fundamental challenge in robot-assisted minimally invasive surgery. Although recent…
SRT-H: A Hierarchical Framework for Autonomous Surgery via Language Conditioned Imitation Learning
Ji Woong Kim, Juo-Tung Chen, Pascal Hansen +11
Research on autonomous surgery has largely focused on simple task automation in controlled environments. However, real-world surgical applications demand dexterous manipulation ove…
Agent Laboratory: Using LLM Agents as Research Assistants
Samuel Schmidgall, Yusheng Su, Ze Wang +7
Historically, scientific discovery has been a lengthy and costly process, demanding substantial time and resources from initial conception to final results. To accelerate scientifi…
AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments
Samuel Schmidgall, Rojin Ziaei, Carl Harris +3
Evaluating large language models (LLM) in clinical scenarios is crucial to assessing their potential clinical utility. Existing benchmarks rely heavily on static question-answering…
MedBrowseComp: Benchmarking Medical Deep Research and Computer Use
Shan Chen, Pedro Moreira, Yuxin Xiao +6
Large language models (LLMs) are increasingly envisioned as decision-support tools in clinical practice, yet safe clinical reasoning demands integrating heterogeneous knowledge bas…