Stop-word Based Contextual Auditing to Identify Inconsistencies in SNOMED

Stop-word Based Contextual Auditing to Identify Inconsistencies in SNOMED
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基于停用词的上下文审计来识别 SNOMED 中的不一致之处

DOI：
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发表时间：
2020
期刊：
SWH@ISWC
影响因子：
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通讯作者：
M. Bertolotto
M. Bertolotto
中科院分区：
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文献类型：
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作者：
Rashmi Burse;G. Mcardle;M. Bertolotto

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. SNOMED是最广泛采用的临床术语系统之一。然而，SNOMED中的不完整表示和建模不一致性正在阻止医疗保健应用充分发挥其潜力。本文提出了一种新的基于停用词的上下文审计方法，以确定潜在的不一致的建模SNOMED概念。试点研究方法的结果表明，这种方法有很大的潜力。使用该方法识别的缺失属性关系的百分比高达69.56%，识别的缺失层次关系的百分比为28.26%。本文提出的审核方法可作为国际卫生术语标准制定组织的补充质量保证检查，以提高SNOMED的质量。
. SNOMED is one of the most widely adopted Clinical Terminology systems. However, incomplete representations and modelling inconsistencies in SNOMED are preventing healthcare applications from exploiting its full potential. This paper presents a novel stop-word based contextual auditing method to identify potential inconsistencies in the modelling of SNOMED concepts. The results of a pilot study method show promising potential with this method. The percentage of identified missing attribute relationships using this method is as high as 69.56% and for identified missing hierarchical relationships it is 28.26%. The auditing method proposed in this paper can act as a supplementary Quality Assurance check in the International Health Terminology Standards Development Organization’s effort to improve the quality of SNOMED.