SURGENT 解决了手术场景中 AI 辅助的隐私和可追溯性痛点，做医疗 AI 或手术辅助系统的开发者可以直接参考其多智能体架构和记忆设计。
SURGENT 是一个面向围手术期全流程的多智能体辅助系统，由 Tree-of-Thought 规划器、多科室协作智能体和检索增强推理模块组成。它通过创新的记忆设计管理长期患者病史和短期工作摘要，解决了大语言模型在手术应用中输入长度限制、记忆不完整和可追溯性差的问题。在病例分析、手术计划模拟、安全监测、并发症风险评估和康复指导五项任务中，SURGENT 表现优于基线 LLM 和现有医疗多智能体框架。消融实验显示，DeepSeek 作为本地可部署的骨干模型，能实现隐私保护部署。该系统为智能、公平且安全的手术辅助提供了实用且可信的进展。
SURGENT: A Surgical Multi-Agent Assistance System Across the Perioperative Workflow
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. Experimental evaluations across five key perioperative tasks - case analysis, surgical plan simulation, safety monitoring, complication risk assessment, and rehabilitation guidance - show that SURGENT outperforms baseline LLMs and existing medical multi-agent frameworks, yielding recommendations more closely aligned with patient histories. Ablation studies further highlight the advantage of DeepSeek as a locally deployable backbone model, enabling privacy-preserving deployment without reliance on centralized services. These results position SURGENT as a practical and trustworthy advancement toward intelligent, equitable, and secure surgical assistance systems.