西安交通大学学报（医学版）2026，Vol.47Issue(3)：424-432,9.DOI:10.7652/jdyxb202603004
基于决策树分析模型大数据治理的危重病情AI预警
AI early warning of critical illness based on decision tree analysis model data governance
摘要
Abstract
Objective To introduce 5G and big data governance technology to build an AI early warning system capable of processing multi-level and multi-type medical data in a timely manner,aiming to detect and warn critical illnesses at an early stage.Methods 5G modules were used to collect real-time bedside ICU data,which underwent standardized processing.Key features were selected using a decision tree algorithm,and both general and personalized early warning models for critical conditions were constructed by integrating recurrent neural networks(RNNs).The model's alerts were pushed in real-time to healthcare staff terminals via an integrated platform.Results A total of 4 053 patients were included(3 022 in the Manual Group and 1 031 in the AI Group).Compared to manual warning,the overall AI warning model significantly shortened the intervention initiation time(median:2.8 minutes vs.4.0 minutes,P<0.01),improved the intervention success rate(median:72.9%vs.52.6%,P<0.01),and reduced the complication rate(median:28.2%vs.42.7%,P<0.01).The model achieved an area under the curve(AUC)of 0.845,with sensitivity of 87.7%and specificity of 68.0%.After six months of learning and optimization,the model's AUC increased to 0.857.Conclusion The AI-based early warning model,built upon 5G technology and big data governance,can effectively achieve early warning of critical conditions in the ICU and improve clinical outcomes,and thus holds potential for clinical promotion.关键词
5G/大数据治理/决策树模型/危重病情/人工智能(AI)/预警模型/机器学习/ICUKey words
5G/big data governance/decision tree model/critical illness/artificial intelligence(AI)/early warning model/machine learning/ICU分类
医药卫生引用本文复制引用
翁成骐,陈斌..基于决策树分析模型大数据治理的危重病情AI预警[J].西安交通大学学报（医学版）,2026,47(3):424-432,9.基金项目
浙江省卫生信息学会重点项目资助(No.2025XHAQ-Z04) （No.2025XHAQ-Z04）
杭州市科技局项目基金(No.2023WJC296)Supported by Key Project Fund of Zhejiang Medical Informatics Association(No.2025XHAQ-Z04)and Project Fund of Hangzhou Science and Technology Bureau(No.2023WJC296) （No.2023WJC296）
