面向临床决策支持系统的医疗文本分析模型  

A medical text analysis model for clinical decision support systems

作　　者：黄琦麟 蒋理[2] 罗义兰 徐治强 利节[1] Huang Qilin;Jiang Li;Luo Yilan;Xu Zhiqiang;Li Jie(Chongqing University of Science and Technology,Chongqing 401331,China;The First Affiliated Hospital of Chongqing Medical University,Chongqing 400042,China;Chongqing Zhongke Accelerated Business Incubator Co.,Ltd.,Chongqing 402760,China)

机构地区：[1]重庆科技学院,重庆401331 [2]重庆医科大学附属第一医院,重庆400042 [3]重庆重科加速创业孵化器有限公司,重庆402760

出　　处：《电子技术应用》2023年第5期57-61,共5页Application of Electronic Technique

基　　金：重庆市自然科学基金面上项目(cstc2020jcyj-msxmX0683);重庆市教委科学技术研究项目(KJQN201901550);重庆市研究生科研创新项目(YKJCX2120822)。

摘　　要：医疗文本的特征提取及分析在建设临床决策支持系统方面具有较大的实用价值。针对包含各种术语和缩写的原始医疗文本难以提取特征的情况,提出了一种基于BERT与Word2vec的医疗文本分析模型。该模型对医疗病历中关键医疗实体进行识别,基于知识建立权重评分机制,对医学文本进行语义分析。实验数据表明,模型在医疗文本特征提取方面具有一定优势,对高血压性脑出血病历的分析诊断性能良好,能有效应用于临床决策支持系统。Feature extraction and analysis of medical text is of great practical value in building clinical decision support systems.A medical text analysis model based on BERT and Word2vec is proposed for the situation that raw medical texts containing various terms and abbreviations are difficult to extract features.The model extracts key medical entities from medical records and establishes a weight scoring mechanism based on knowledge for semantic analysis of medical texts.The experimental data show that the model has certain advantages in medical text feature extraction,good performance in the analysis and diagnosis of hypertensive intracerebral hemorrhage medical records,and can be effectively used in clinical decision support systems.

关 键 词：临床决策支持系统 命名实体识别 特征提取 语义分析 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]