电子病历在临床诊断与治疗中的应用日益广泛,如何有效利用电子病历系统中的大量数据辅助医生进行分析与诊断,是一个非常重要的问题.传统的基于索引的检索方法已不能满足对大型电子病历数据库检索的需要,将基于本体的向量空间模型引入到电子病历中进行研究,是一项非常有意义的工作.在分析传统电子病历检索方法不足的基础上,结合模糊本体概念,提出一种基于本体的向量空间模型.该方法充分利用了模糊本体中隶属度的概念,对查询语句和电子病历关键词向量空间模型进行模糊本体概念映射及概念相似度计算.最后通过数值实验,对该方法在查全率和查准率方面进行了性能分析,证明其具有良好性能.%Electronic medical record has been increasingly applied in clinical diagnosis and treatment.It is very important to make use of large numbers of dates in electronic medical record system in order to help clinician to analyze and diagnose.The traditional index retrieval techniques are not fit for retrieving large scale electronic medical record databases.It is a very promising idea to introduce Ontology-based Vector Space Model into Electronic medical record Based on the deficiency of traditional Electronic Medical record method and the concept of fuzzy ontology, we present a Ontology-based Vector Space Model.In this method, concept mapping and similarity calculating are made based on the membership-degree concept of fuzzy ontology, which make it possible for us to analyze image on concept level.Finally experiments are carried out to test it performance, and the result shows its efficiency.
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