中国感染控制杂志2026，Vol.25Issue(5)：631-637,7.DOI:10.12138/j.issn.1671-9638.20262906
基于DeepSeek的医院感染智能判定系统构建及效能评价
Construction and performance of DeepSeek-based artificial intelligence judgement system for healthcare-associated infection
摘要
Abstract
Objective To construct an artificial intelligence(AI)judgement system for healthcare-associated infec-tion(HAI)based on the DeepSeek large language model,evaluate its performance differences from traditional indi-vidual-based manual review.Methods A single-center retrospective study was conducted,medical records of discharged patients from the Second Hospital of Dalian Medical University between January and June 2025 were included for analysis,the blinded consensus of 5 senior infection control experts was used as the gold standard to judge HAI,the differences in sensitivity,specificity,accuracy,area under the curve(AUC),and Kappa values of the AI system and individual review were compared,subgroup analysis based on infection sites and error type cate-gorization was also performed.Results According to the expert gold standard judgement,136 cases were positive and 184 cases were negative for HAI in this study.The performance comparison showed that the AI system outper-formed individual judgement in various performance indicators:sensitivity(92.6%vs 84.6%),accuracy(93.8%vs 89.1%),AUC(0.976 vs 0.897),and Kappa value(0.869 vs 0.776),with differences being statistically signi-ficant(all P<0.05).The sensitivity of the AI system to different infection sites remained above 94%,especially in bloodstream infection,which was significantly superior to manual review(94.7%vs 73.7%,P=0.044).Analysis of error types revealed that AI misjudgements were mainly caused by atypical clinical manifestations,while manual underreporting was often caused by negligence in reading medical records.Conclusion The DeepSeek-based AI judgement system for HAI demonstrates high judgement performance and stability,and can significantly improve the sensitivity and standardization of HAI recognition.The human-AI collaborative model of"AI initial screening-manual final review"can serve as an intelligent solution for HAI prevention and control.关键词
人工智能/智能监测/DeepSeek/医院感染/大语言模型Key words
artificial intelligence/intelligent monitoring/DeepSeek/healthcare-associated infection/large language model分类
医药卫生引用本文复制引用
范鹏超,高华聪,王倩,刘欣奕,刘文芝..基于DeepSeek的医院感染智能判定系统构建及效能评价[J].中国感染控制杂志,2026,25(5):631-637,7.基金项目
大连医科大学附属第二医院机关管理1+x课题(2024QNGL04) （2024QNGL04）
