[1]胡德华,方浩,周宇葵,等.基于诊疗知识库和电子病历的整合推荐方法研究[J].中国医学物理学杂志,2019,36(4):492-496.[doi:DOI:10.3969/j.issn.1005-202X.2019.04.024]
　HU Dehua,FANG Hao,ZHOU Yukui,et al. A hybrid recommendation method based on medical knowledge base and electronic medical records[J].Chinese Journal of Medical Physics,2019,36(4):492-496.[doi:DOI:10.3969/j.issn.1005-202X.2019.04.024]
点击复制

基于诊疗知识库和电子病历的整合推荐方法研究()
分享到：

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
36卷
期数:
2019年第4期
页码:
492-496
栏目:
其他（激光医学等）
出版日期:
2019-04-25

文章信息/Info

Title:
 A hybrid recommendation method based on medical knowledge base and electronic medical records
文章编号:
1005-202X（2019）04-0492-05
作者:
胡德华; 方浩; 周宇葵; 罗爱静
中南大学生命科学学院医药信息系， 湖南 长沙 410083
Author(s):
HU Dehua;  FANG Hao;  ZHOU Yukui;  LUO Aijing
Department of Medical Information, School of Life Sciences, Central South University, Changsha 410083, China
关键词:
临床知识库; 电子病历; 协同过滤; 内容过滤
Keywords:
Keywords: medical knowledge base;  electronic medical record;  collaborative filtering;  content filtering
分类号:
R319；TP391
DOI:
DOI:10.3969/j.issn.1005-202X.2019.04.024
文献标志码:
A
摘要:
目的：探索一种基于临床诊疗知识库和电子病历为患者推荐诊疗相关知识的有效方法。方法：引入诊疗知识库的内容过滤结合电子病历建立整合评分矩阵，融合基于电子病历的患者协同过滤（PbCF）和疾病诊断的协同过滤（DbCF）结果，构建整合推荐方法，减少预测结果的误差。以平均绝对百分误差（MAPE）作为评价指标，对整合推荐方法与独立PbCF、DbCF预测结果进行评估比较。结果：整合推荐方法的MAPE要小于PbCF和DbCF。局限于所选诊疗知识库的高血压疾病种类覆盖面不及电子病历中高血压患者所涉及的疾病种类，扩大诊疗知识库疾病覆盖面对推荐结果的影响仍需进一步探讨。结论：整合推荐方法比独立的PbCF、DbCF效果更好，为患者推荐疾病诊疗知识，具有良好的应用前景。
Abstract:
Abstract: Objective To explore an effective method for providing recommendation knowledge related to diagnosis and treatment for patients based on medical knowledge base and electronic medical records. Methods The content filtering method of medical knowledge base was combined with electronic medical records to establish an integrated scoring matrix. The fusion of the results obtained with patient-based collaborative filtering and diagnosis-based collaborative filtering was used to construct a hybrid recommendation method, so as to reduce the error of prediction results. With mean absolute percentage error as the evaluation index, the prediction results obtained with hybrid recommendation method, patient-based collaborative filtering and diagnosis-based diagnostic collaborative filtering were evaluated. Results The average absolute percent error of hybrid recommendation method was lower than that of patient-based collaborative filtering and diagnosis-based collaborative filtering. The limitation of this study is that the types of hypertensive diseases in medical knowledge base were less than those in electronic medical records, and that the effects of the disease coverage on the recommendation results remained to be further explored. Conclusion The hybrid recommendation method which is superior to patient-based collaborative filtering and diagnosis-based diagnostic collaborative filtering can be used to provide medical knowledge for patients, having a good application prospect.

相似文献/References:

[1]辛华坤,焦 青,胡 磊,等.基于SQL SERVER2008的眼科电子病历系统的研制[J].中国医学物理学杂志,2014,31(01):4646.[doi:10.3969/j.issn.1005-202X.2014.01.012]
[2]李小华,刘晓辉,冯前进,等.基于电子病历的医院信息平台的关键技术[J].中国医学物理学杂志,2014,31(02):4772.[doi:10.3969/j.issn.1005-202X.2014.02.013]
[3]刘莉,姚京京,李俊,等. 基于共词分析和可视化的高血压疾病关联性挖掘[J].中国医学物理学杂志,2019,36(5):614.[doi:DOI:10.3969/j.issn.1005-202X.2019.05.024]
　LIU Li,YAO Jingjing,LI Jun,et al. Hypertension related association mining based on co-word analysis and visualization[J].Chinese Journal of Medical Physics,2019,36(4):614.[doi:DOI:10.3969/j.issn.1005-202X.2019.05.024]
[4]安莹,黄能军,杨荣,等. 基于深度学习的心血管疾病风险预测模型[J].中国医学物理学杂志,2019,36(9):1103.[doi:DOI:10.3969/j.issn.1005-202X.2019.09.021]
　AN Ying,HUANG Nengjun,YANG Rong,et al. Deep learning-based model for risk prediction of cardiovascular diseases[J].Chinese Journal of Medical Physics,2019,36(4):1103.[doi:DOI:10.3969/j.issn.1005-202X.2019.09.021]
[5]韦彩萍,李翔,翁梦晴,等.机器学习在电子病历中应用的可视化分析[J].中国医学物理学杂志,2023,40(4):521.[doi:DOI:10.3969/j.issn.1005-202X.2023.04.019]
　WEI Caiping,LI Xiang,WENG Mengqing,et al.Visualization analysis on machine learning application in electronic medical record[J].Chinese Journal of Medical Physics,2023,40(4):521.[doi:DOI:10.3969/j.issn.1005-202X.2023.04.019]

备注/Memo

备注/Memo:
【收稿日期】2019-01-15
【基金项目】国家社科基金重点项目（17ZDA037）；教育部-中国移动联合实验室移动医疗项目；万方数据-中南大学医学知识服务创新联合实验室规划项目；中南大学中央高校基本科研业务费专项资金（2018zzts303）
【作者简介】胡德华，教授，博士生导师，研究方向：医药信息管理、医学数据挖掘、信息检索、信息查询行为等，E-mail: hudehua2008@qq.com
【通信作者】罗爱静，教授，博士生导师，E-mail: luoaj@mail.csu.edu.cn
更新日期/Last Update: 2019-04-23