Assélé Kama Ariane, Choquet Rémy, Mels Giovanni, Daniel Christel, Charlet Jean, Jaulent Marie-Christine
INSERM UMR_S 872 Eq 20, Université Pierre et Marie Curie, Paris, France.
Stud Health Technol Inform. 2013;192:142-6.
Clinical data captured in hospital information systems may be unusable in their original format due to missing information or knowledge. The use of external resources (e.g. domain ontology) could be a way of dealing with this lack of knowledge. Our study thus aimed to develop a framework allowing a user to perform medical queries in the context of infectious diseases. By creating an interaction between a knowledge source and clinical data, using semantic and semantic web tools and methods, the users are able to perform queries on a database to obtain results about antibiotic resistance. This work has been performed in the context of the DebugIT European project that aims to control and monitor the antibioresistance growth via a semantic interoperability platform. The results obtained by the use of different semantic web tools were quantitatively evaluated by comparison of the number of results and the query execution time. We have compared our approach with classic business intelligence approaches in terms of usability and functionality.
医院信息系统中捕获的临床数据可能由于信息或知识缺失而无法以原始格式使用。利用外部资源（如领域本体）可能是解决这种知识匮乏的一种方法。因此，我们的研究旨在开发一个框架，允许用户在传染病背景下执行医学查询。通过使用语义和语义网工具及方法，在知识源和临床数据之间建立交互，用户能够对数据库执行查询，以获取有关抗生素耐药性的结果。这项工作是在DebugIT欧洲项目的背景下进行的，该项目旨在通过语义互操作性平台控制和监测抗生素耐药性的增长。通过比较结果数量和查询执行时间，对使用不同语义网工具获得的结果进行了定量评估。我们已在可用性和功能方面将我们的方法与经典商业智能方法进行了比较。
