Using semantic and structural properties of the Unified Medical Language System to discover potential terminological relationships.
Using semantic and structural properties of the Unified Medical Language System to discover potential terminological relationships.
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DOI：
10.1197/jamia.m2931
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发表时间：
2009-05
期刊：
影响因子：
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通讯作者：
Chintan Patel;J. Cimino
中科院分区：
文献类型：
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作者：
Chintan Patel;J. Cimino
目的利用《统一医学语言系统(UMLS)元词表》中的语义和结构特征来刻画和发现潜在的关系。设计UMLS整合了几个生物医学术语的知识。这些知识可以用来发现概念之间的隐含语义关系。在本文中，作者提出了一种与问题无关的发现潜在术语关系的方法，该方法利用间接关系路径的语义抽象来对网络理论度量进行分类和分析，如拓扑重叠、优先连接、图划分和间接路径数量。使用UMLS的不同版本，作者评估了所提出的方法预测新增加的关系的能力。测量分类准确度，精确度-召回。结果基于语义抽象的分类器(分类正确率为91%)、间接路径平均数、偏好依恋和图分割识别潜在关系具有很强的区分性特征。对于2005至2007年间添加到UMLS后续版本中的新关系，建议的关系预测算法在前10名中的召回率为56%。结论UMLS有足够的知识来发现潜在的术语关系。
OBJECTIVE To use the semantic and structural properties in the Unified Medical Language System (UMLS) Metathesaurus to characterize and discover potential relationships. DESIGN The UMLS integrates knowledge from several biomedical terminologies. This knowledge can be used to discover implicit semantic relationships between concepts. In this paper, the authors propose a problem-independent approach for discovering potential terminological relationships that employs semantic abstraction of indirect relationship paths to perform classification and analysis of network theoretical measures such as topological overlap, preferential attachment, graph partitioning, and number of indirect paths. Using different versions of the UMLS, the authors evaluate the proposed approach's ability to predict newly added relationships. MEASUREMENTS Classification accuracy, precision-recall. RESULTS Strong discriminative characteristics were observed with a semantic abstraction based classifier (classification accuracy of 91%), the average number of indirect paths, preferential attachment, and graph partitioning to identify potential relationships. The proposed relationship prediction algorithm resulted in 56% recall in top 10 results for new relationships added to subsequent versions of the UMLS between 2005 and 2007. CONCLUSIONS The UMLS has sufficient knowledge to enable discovery of potential terminological relationships.