A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.
A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.
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DOI：
10.1093/jamia/ocaa123
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发表时间：
2020-10-01
期刊：
影响因子：
--
通讯作者：
Cui L
中科院分区：
文献类型：
--
作者：
Zheng F;Shi J;Yang Y;Zheng WJ;Cui L
统一医学语言系统（UMLS）集成了各种源术语，以支持生物医学信息系统之间的互操作性。在这篇文章中，我们介绍了一种新的转换为基础的审计方法，利用UMLS知识，系统地识别源术语中缺失的层次IS-A关系。给定UMLS中的概念名称，我们首先识别其基本和次要名词组块。对于每个识别的名词块，我们生成比名词块更一般的替换候选。然后，我们用它们的替换候选者替换名词块，以生成新的潜在概念名称，这些名称可以作为原始概念的超类型。如果新生成的名称是与原始概念相同的源术语中的现有概念名称，则识别原始概念与新概念之间的潜在缺失的IS-A关系。将我们基于转换的方法应用于UMLS（2019 AB版本）中的英语概念名称，在13个源术语中检测到总共39359个潜在缺失的IS-A关系。领域专家评估了在SNOMED CT（美国版）中识别的200个潜在缺失的IS-A关系和在Gene Ontology中识别的100个IS-A关系的随机样本。领域专家确认了200个潜在缺失IS-A关系中的173个和100个潜在缺失IS-A关系中的63个，这表明我们的方法对于SNOMED CT和Gene Ontology分别实现了86.5%和63%的精确度。我们的研究结果表明，我们的转换为基础的方法是有效的，在确定丢失的IS-A关系的UMLS源术语。
The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical information systems. In this article, we introduce a novel transformation-based auditing method that leverages the UMLS knowledge to systematically identify missing hierarchical IS-A relations in the source terminologies. Given a concept name in the UMLS, we first identify its base and secondary noun chunks. For each identified noun chunk, we generate replacement candidates that are more general than the noun chunk. Then, we replace the noun chunks with their replacement candidates to generate new potential concept names that may serve as supertypes of the original concept. If a newly generated name is an existing concept name in the same source terminology with the original concept, then a potentially missing IS-A relation between the original and the new concept is identified. Applying our transformation-based method to English-language concept names in the UMLS (2019AB release), a total of 39 359 potentially missing IS-A relations were detected in 13 source terminologies. Domain experts evaluated a random sample of 200 potentially missing IS-A relations identified in the SNOMED CT (U.S. edition) and 100 in Gene Ontology. A total of 173 of 200 and 63 of 100 potentially missing IS-A relations were confirmed by domain experts, indicating that our method achieved a precision of 86.5% and 63% for the SNOMED CT and Gene Ontology, respectively. Our results showed that our transformation-based method is effective in identifying missing IS-A relations in the UMLS source terminologies.
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DOI：
10.1093/jamia/ocw175
发表时间：
2017-07-01
期刊：
Journal of the American Medical Informatics Association : JAMIA
影响因子：
--
作者：
Cui L;Zhu W;Tao S;Case JT;Bodenreider O;Zhang GQ
通讯作者：
Zhang GQ
影响因子：
3.2
作者：
Adamusiak, Tomasz;Shimoyama, Naoki;Shimoyama, Mary
通讯作者：
Shimoyama, Mary
DOI：
10.1136/jamia.2001.0080351
发表时间：
2001-07-01
影响因子：
6.4
作者：
Achour, SL;Dojat, M;Lepage, E
通讯作者：
Lepage, E
影响因子：
4.5
作者：
Martinez, David;Otegi, Arantxa;Agirre, Eneko
通讯作者：
Agirre, Eneko
影响因子：
14.9
作者：
Bodenreider, O
通讯作者：
Bodenreider, O