Jaulent Marie-Christine, Alecu Iulian
INSERM, UMR_S 872, eq.20 Paris, France.
Stud Health Technol Inform. 2009;150:522-6.
In this work, we present a methodology for evaluating an ontology designed in a previous study to describe adverse drug reactions. We evaluate it in term of its fitness for grouping cases in pharmacovigilance. We define as gold standard the Standardized MedDRA Queries (SMQs) developed manually to group terms representing similar medical conditions. We perform an automatic search in the ontology in order to retrieve concepts related to the medical conditions. An optimal query is built for each medical condition. The evaluation relies on the comparison between the terms in the SMQ and the terms subsumed by the query. The result is quantified by sensitivity and specificity. We applied this methodology for 24 SMQs and we obtain a mean sensitivity of 0.82. This work allows validating the semantic resource and provides, in perspective, tools to maintain the ontology while the knowledge is evolving.
在这项工作中，我们提出了一种方法，用于评估在先前研究中设计的用于描述药物不良反应的本体。我们从其在药物警戒中对病例分组的适用性方面对其进行评估。我们将手动开发的用于对代表相似医疗状况的术语进行分组的标准化医学术语集（SMQ）定义为金标准。我们在本体中进行自动搜索，以检索与医疗状况相关的概念。为每个医疗状况构建一个最优查询。评估依赖于SMQ中的术语与查询所包含的术语之间的比较。结果通过敏感性和特异性进行量化。我们将此方法应用于24个SMQ，获得了0.82的平均敏感性。这项工作有助于验证语义资源，并前瞻性地提供在知识不断发展时维护本体的工具。
