arXiv：cs.CL· Ziyang Ling, Shuyu Lu, Ziyi Chen·· 6 小时前
PRISMATIC：面向临床决策中多智能体治疗交互的处方风险检查系统
PRISMATIC : Prescription Risk Inspection System for Multi-Agent Treatment Interaction in Clinical Decision-Making
AI 导读
PRISMATIC 是一个面向多病共存患者的多智能体处方系统，采用黑板架构让代表不同工作流角色的专精智能体协作生成并迭代优化用药方案。系统引入 DSWA 与 DFPC 两种协调机制，分别根据历史病例结果调整智能体权重、通过迭代反馈消除处方冲突。基于 MIMIC-IV 数据库的患者记录实验显示，PRISMATIC 相比强 LLM 基线显著减少了药物冲突、提升了处方覆盖率和治疗一致性。
正文
Abstract:Medical prescribing errors for multimorbid patients, who require complex drug regimens, are a major patient safety concern. These errors often stem from fragmented decision-making across medical specialties, a critical coordination failure that leads to adverse drug events and rehospitalizations. To address this coordination challenge, we introduce PRISMATIC, a multi-agent architecture where specialized agents, each representing a workflow role, collaboratively generate and refine treatment plans. Operating on a blackboard architecture, the system first structures patient information from clinical notes, then iteratively develops safe, rational, and interpretable drug regimens. The agents' collaboration is governed by two novel adaptive coordination mechanisms: (1) Dynamic Self-Updating Weight Adjustment (DSWA), a long-term mechanism that adjusts the influence weights of agents based on historical case outcomes, enabling the system to adapt and trust more reliable specialists over time. (2) Discrepancy Feedback Precise Calibration (DFPC), a short-term mechanism where agents provide iterative feedback to resolve disagreements and eliminate prescription conflicts for the current patient. Experiments on patient records from the MIMIC-IV database show that PRISMATIC significantly reduces drug conflicts, improves prescription coverage, and enhances treatment consistency compared to strong LLM baselines. Our work demonstrates that structuring clinical co-treatment as a multi-agent coordination problem offers a promising path toward safer and more coherent multidisease management.
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.19762 [cs.CL] |
| (or arXiv:2610.19762v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2610.19762 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Ziyi Chen [view email]
[v1]
Wed, 14 Oct 2026 08:17:05 UTC (6,297 KB)
来源：arXiv：cs.CL · arxiv.org