Miñarro-Giménez Jose Antonio, Schulz Stefan
Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria.
Stud Health Technol Inform. 2018;247:666-670.
Organised repositories of published scientific literature represent a rich source for research in knowledge representation. MEDLINE, one of the largest and most popular biomedical literature databases, provides metadata for over 24 million articles each of which is indexed using the MeSH controlled vocabulary. In order to reuse MeSH annotations for knowledge construction, we processed this data and extracted the most relevant patterns of assigned descriptors over time. The patterns consist of UMLS semantic groups related to the MeSH headings together with their associated MeSH subheadings. Then, we connected the patterns with the most frequent predicates in their corresponding MEDLINE abstracts. Thereafter, we conducted a time series analysis of the extracted patterns from MEDLINE records and their associated predicates in order to study the evolution of manual MeSH indexing. The results show an increasing diversity of the assigned MESH terms over time, along with the increase of scientific publication per year. We obtained evidence of consistency of the relevant predicates associated with the extracted patterns. Moreover, for the most frequent patterns some predicates predominate over others such as Treats between substances and disorders, Causes between pairs of disorders, or Interacts between pairs of substances.
已发表科学文献的有组织存储库是知识表示研究的丰富资源。MEDLINE是最大且最受欢迎的生物医学文献数据库之一，为超过2400万篇文章提供元数据，每篇文章都使用医学主题词表（MeSH）受控词汇进行索引。为了在知识构建中重用MeSH注释，我们处理了这些数据，并随着时间的推移提取了分配描述符的最相关模式。这些模式由与MeSH标题相关的UMLS语义组及其相关的MeSH副标题组成。然后，我们将这些模式与相应MEDLINE摘要中最频繁出现的谓词联系起来。此后，我们对从MEDLINE记录中提取的模式及其相关谓词进行了时间序列分析，以研究人工MeSH索引的演变。结果表明，随着时间的推移，分配的MeSH术语的多样性不断增加，同时每年的科学出版物数量也在增加。我们获得了与提取模式相关的相关谓词一致性的证据。此外，对于最常见的模式，一些谓词比其他谓词更占主导地位，例如物质与疾病之间的“治疗”、疾病对之间的“导致”或物质对之间的“相互作用”。
