SURGENT: A Surgical Multi-Agent Assistance System Across the Perioperative Workflow 文章

ArXiv CS.CL2026-05-29NEWSen作者: Dongsheng Shi, Yue Li, Xin Yi, Yongyi Cui, Huawei Feng, Linlin Wang

摘要

arXiv:2605.29368v1 Announce Type: new Abstract: The intricate nature of modern surgical care necessitates intelligent systems that can synthesize extensive patient records, support collaborative decision-making, and provide transparent, auditable reasoning across the entire perioperative workflow. Although web-based Large Language Models (LLMs) possess advanced reasoning capabilities, they are ill-equipped for surgical applications due to critical limitations: input length constraints, incomplete memory management, and limited traceability. To address this issue, we present SURGENT, a surgical multi-agent assistance system that combines a Tree-of-Thought planner, multi-department collaboration agents, and retrieval-augmented reasoning with clinical guidelines and biomedical literature. SURGENT features a novel memory design that manages both long-term patient histories and short-term working summaries, enabling more complete, contextualized, and consistent reasoning.