计算机与现代化

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基于电子病历利用矩阵乘法构建医生推荐模型

  

  1. (重庆医科大学附属第一医院信息中心,重庆400016)
  • 收稿日期:2018-12-24 出版日期:2019-06-14 发布日期:2019-06-14
  • 作者简介:杨晓夫(1989-),男,重庆垫江人,助理工程师,硕士,研究方向:医疗大数据分析,智慧医院,软件工程,E-mail: yxfshard@163.com; 秦函书(1987-),女,硕士,研究方向:医疗大数据分析,智慧医院,软件工程。

Building Doctor Recommendation Model by Matrix Multiplication #br# Based on Electronic Medical Record

  1. (Information Center, First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China)
  • Received:2018-12-24 Online:2019-06-14 Published:2019-06-14

摘要:
摘要:当前医疗机构缺乏通过互联网进行医疗资源推荐的有效渠道。同时,由于医疗应用场景的复杂性与多样性致使传统推荐算法面向医疗领域推荐质量不高。因此,提出基于电子病历利用矩阵乘法构建医生推荐模型。推荐模型以电子病历为研究对象,使用朴素贝叶斯分类器获取意向科室;根据症状、诊断、结论等信息构建意向科室医生-疾病矩阵与疾病-患者矩阵,利用矩阵乘法计算推荐结果。实验结果表明,推荐模型达到最佳性能时准确率为97.3%,平均准确率可以达到95.6%。

关键词: 医疗, 推荐模型, 电子病历, 矩阵

Abstract:  Currently, medical institutions lack effective channels to recommend medical resources through Internet. At the same time, due to the complexity and diversity of medical resource application scenarios, the quality of traditional recommendation algorithms for medical field recommendation is not high. Therefore, a doctor recommendation model based on electronic medical records is proposed by matrix multiplication. The recommendation model takes electronic medical records as research object and uses naive Bayesian classifier to obtain intention departments. According to the information of symptoms, diagnosis and conclusions, the doctor-disease matrix and disease-patient matrix of intention departments are constructed, and the recommended results are calculated by matrix multiplication. The experimental results show that the accuracy of the recommended model is 97.3% and the average accuracy is 95.6%.

Key words: medical, recommendation model, electronic medical record, matrix

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