CISMeF, Rouen University Hospital, Cour Leschevin, Porte 21, 3ème étage, 1 rue de Germont, 76031 Rouen Cedex, France.
BMC Med Inform Decis Mak. 2012 Feb 29;12:12. doi: 10.1186/1472-6947-12-12.
PubMed is the main access to medical literature on the Internet. In order to enhance the performance of its information retrieval tools, primarily non-indexed citations, the authors propose a method: expanding users' queries using Unified Medical Language System' (UMLS) synonyms i.e. all the terms gathered under one unique Concept Unique Identifier.
This method was evaluated using queries constructed to emphasize the differences between this new method and the current PubMed automatic term mapping. Four experts assessed citation relevance.
Using UMLS, we were able to retrieve new citations in 45.5% of queries, which implies a small increase in recall. The new strategy led to a heterogeneous 23.7% mean increase in non-indexed citation retrieved. Of these, 82% have been published less than 4 months earlier. The overall mean precision was 48.4% but differed according to the evaluators, ranging from 36.7% to 88.1% (Inter rater agreement was poor: kappa = 0.34).
This study highlights the need for specific search tools for each type of user and use-cases. The proposed strategy may be useful to retrieve recent scientific advancement.
PubMed 是互联网上获取医学文献的主要途径。为了提高其信息检索工具的性能,主要是非索引引文,作者提出了一种方法:使用统一医学语言系统(UMLS)同义词扩展用户的查询,即收集在一个唯一概念标识符下的所有术语。
使用构建的查询评估了这种方法,这些查询强调了这种新方法与当前 PubMed 自动术语映射之间的区别。四位专家评估了引文的相关性。
使用 UMLS,我们能够在 45.5%的查询中检索到新的引文,这意味着召回率略有提高。新策略导致非索引引文的平均检索量增加了 23.7%,其中 82%的引文发表时间不到 4 个月。总体平均精度为 48.4%,但因评估者而异,范围从 36.7%到 88.1%(评估者之间的一致性很差:kappa = 0.34)。
这项研究强调了为每种类型的用户和用例提供特定搜索工具的必要性。所提出的策略可能有助于检索最新的科学进展。