新医学2026，Vol.57Issue(4)：329-338,10.DOI:10.12464/j.issn.0253-9802.2026-0087
基于糖尿病足多阶段病程管理的AI智能体构建与验证
Construction and validation of an AI agent for multistage disease-course management in diabetic foot
摘要
Abstract
Objective To investigate the application value of a tool-driven artificial intelligence(AI)agent in clinical decision-making across multiple stages of the disease course in patients with diabetic foot.Methods Using the large language model(LLM)Qwen3-max as the reasoning engine,an AI agent adaptable to repeated follow-up scenarios in diabetic foot was constructed by integrating the ReAct framework,retrieval-augmented generation(RAG)technology,and multimodal data-processing tools.Validation was performed based on retrospective data from 34 patients with diabetic foot(a total of 140 visits).Performance differences were compared among the AI agent,the native large language model Qwen3-max,and the medical LLM Baichuan-M1-14B.Results The clinical practicality score of the AI agent reached 8.29±0.91,significantly higher than that of the Qwen3-max(7.56±0.70,t=4.19,P＜0.001)and Baichuan-M1-14B(7.82±0.67,t=3.67,P＜0.001).Moreover,the advantage became more pronounced as the number of disease-course visits increased.In the high disease-course group(≥7 visits),the AI agent scored 9.50±0.58,exceeding Qwen3-max(7.50±0.58)and Baichuan-M1-14B(8.50±0.58)by 2.00 and 1.60 points,respectively.The AI agent increased the accuracy of diagnosis and staging to 94.1%through RAG technology,reduced the hallucination incidence to 8.7%via the ReAct framework,achieved an automatic recognition accuracy of 95.7%for key indicators,and shortened the time required for disease-course data integration by 88.3%compared with traditional manual methods.Conclusions The AI agent constructed in this study achieved automated and standardized analysis and management of multiple disease-course episodes in diabetic foot,effectively reducing the"hallucination"risk of native LLMs,and can provide solid technical support for early warning,condition monitoring,and individualized treatment of diabetic foot.关键词
AI智能体/糖尿病足/超声检查/多模态数据融合/病程管理Key words
AI agent/Diabetic foot/Ultrasound examination/Multimodal data fusion/Disease-course management引用本文复制引用
李鸯,麦耀锋,陈灿烽,赵志祥,戴志兵,张红艳,谭苏梦源,李奈青..基于糖尿病足多阶段病程管理的AI智能体构建与验证[J].新医学,2026,57(4):329-338,10.基金项目
广东省医学科学技术研究基金项目(B2023205) （B2023205）
广州市科技计划项目(2025A03J3508) （2025A03J3508）
