引用本文:曾红武,王 佳.基于关联关系的电子病历聚类研究[J].中华医学图书情报杂志,2018,27(5):42-45.
基于关联关系的电子病历聚类研究
Association relation-based clustering of electronic medical records
DOI:10.3969/j.issn.1671-3982.2018.05.008
中文关键词:  向量空间模型  关联关系  电子病历  隐语义关系
英文关键词:Vector space model  Association relation  Electronic medical records  Implicit semantic relation
基金项目:重庆市科技计划项目专项“基于互联网的健康服务关键共性技术研发与集成创新”(cstc2015shms-ztzx10011)
作者单位
曾红武 重庆医科大学医学信息学院,重庆 400016 
王 佳 重庆医科大学医学信息学院,重庆 400016 
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中文摘要:
      针对现有的向量空间模型在电子病历聚类时忽略语义关系的不足,提出了一种基于关联关系的电子病历聚类方法:从海量的电子病历中分析特征语的同现概率,根据关联规则分析特征词语的关联关系,挖掘电子病历特征词之间的隐含语义关系,表达电子病历向量,结果表明,基于关联关系的电子病历聚类更为准确。
英文摘要:
      The association relation-based clustering method of electronic medical records (EMR) was put forward in accordance with the ignored semantic relation when the vector space model was used to cluster EMR, namely the co-occurrence probability of characteristic words in the massive EMR was analyzed, the association relation of characteristic words was analyzed according to their association rules, the implicit semantic relation between the characteristic words in EMR was mined and the vector of EMR was expressed. The method was verified, which indicates that the association relation-based clustering method of EMR is more accurate.
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