Martin B K, Rada R
School of Medicine, University of Hawaii, Honolulu 96816.
Med Inform (Lond). 1987 Jul-Sep;12(3):187-201. doi: 10.3109/14639238709044553.
We show how three existing medical knowledge bases: Medical Subject Headings (MeSH), Standardized Nomenclature of Medicine (SNOMED) and Current Medical Information and Technology (CMIT) are mapped into a relational data model and stored on an Apollo workstation and an Intelligent Database Machine. Since two of these knowledge bases have been used in the indexing of medical literature and patient records, they can be useful not only as direct views on the organization of medical concepts but also as tools for the retrieval of documents. In order that the concepts from one knowledge base can be connected to those of the other knowledge base, a method has been developed for the semi-automatic merging of MeSH, SNOMED and CMIT. This method takes advantage of the relational model and the synonyms that are given in SNOMED and CMIT, in order to recommend concepts to be merged. An expert interacts with the system to accept or reject the recommendations of the computer. The method would apply equally well to other knowledge bases and is particularly well-suited for knowledge bases that contain tens of thousands of concepts.
医学主题词表（MeSH）、医学标准化命名法（SNOMED）和当前医学信息与技术（CMIT）映射到关系数据模型中，并存储在阿波罗工作站和智能数据库机器上。由于其中两个知识库已用于医学文献和患者记录的索引编制，它们不仅可作为医学概念组织的直接视图，还可作为文档检索工具。为了使一个知识库中的概念能够与另一个知识库中的概念相连接，已开发出一种用于MeSH、SNOMED和CMIT半自动合并的方法。该方法利用关系模型以及SNOMED和CMIT中给出的同义词，以便推荐要合并的概念。专家与系统交互以接受或拒绝计算机的建议。该方法同样适用于其他知识库，尤其适用于包含数万个概念的知识库。
