西安交通大学学报（医学版）2026，Vol.47Issue(3)：464-470,7.DOI:10.7652/jdyxb202603009
大语言模型预测手术持续时长对手术资源配置管理效率的促进作用
Large language models predict the promoting effect of operation duration on the efficiency of surgical resource allocation and management
摘要
Abstract
Objective To evaluate the potential value of large language models in improving the efficiency of operating room resource utilization by comparing the performance of different large language models in predicting the duration of surgery.Methods A total of 6 154 surgical operation data(mainly including operation name,chief surgeon,and assistant doctor)from Shanghai Chest Hospital from November 2024 to January 2025 were selected for large language models(Qwen-7B,DeepSeek-32B and DeepSeek-671B)training and testing.The LoRA fine-tuning technology,retrieval enhancement generation strategy,and cue word engineering were used to optimize the model;the performance of the model was evaluated by the mean square error,mean absolute error,mean absolute percentage error,and the accuracy of surgery duration prediction.In addition,three hospital managers were invited to perform surgery scheduling with the assistance of large language models,and the auxiliary effect of large language models on surgical resource allocation management was evaluated by comparing the occupancy time of the operating room with that without the assistance of large language models.Results The prediction accuracy of DeepSeek-671B model was 52.06%(Z=-6.695,P<0.001),which was significantly higher than that of Qwen-7B 45.99%(Z=-2.854,P<0.001)and DeepSeek-32B 48.16%(Z=-5.199,P<0.001).Meanwhile,the regression error index of DeepSeek-671B was also better than that of Qwen-7B and DeepSeek-32B(MSE:2 486.11 vs.3 734.31 vs.3 224.89,MAE:34.99 vs.40.31 vs.38.78).Before and after the assistance of the three large language models,the actual operating room occupancy time was reduced by 5.48%,3.37%and 8.26%,respectively,and the rank sum test results showed that the difference was statistically significant(Z=-3.408,P<0.005).Conclusion Predicting the duration of surgery by large language models helps to improve the management efficiency of surgical resource allocation,and hospital managers can arrange the operation sequence more scientifically so as to effectively improve the overall operation efficiency of the operating room.关键词
医院管理/手术资源配置/大语言模型/Qwen/DeepSeek/模型微调/检索增强生成Key words
hospital management/surgical resources allocation/large language model/Qwen/DeepSeek/model fine-tuning/retrieval augmented generation分类
信息技术与安全科学引用本文复制引用
王毅豪,袁骏毅,张蕾,舒婷..大语言模型预测手术持续时长对手术资源配置管理效率的促进作用[J].西安交通大学学报（医学版）,2026,47(3):464-470,7.基金项目
国家卫生健康委医院管理研究所医疗人工智能临床应用研究项目(No.YLXX24AIC003) （No.YLXX24AIC003）
上海申康医院发展中心技术规范化管理和推广项目(No.SHDC22026202) （No.SHDC22026202）
上海市卫生健康委员会智慧医疗专项研究项目(No.2025ZHYL011)Supported by Research Project on Clinical Application of Medical Artificial Intelligence by National Institute for Hospital Administra-tion,National Health Commission of China(No.YLXX24AIC003),Technology Standardization Management and Promotion Project of Shanghai Shenkang Hospital Development Center(No.SHDC22026202),and Special Research Project of Smart Healthcare of Shanghai Health Commission(No.2025ZHYL011) （No.2025ZHYL011）
