Boeker Martin, Stenzhorn Holger, Kumpf Kai, Bijlenga Philippe, Schulz Stefan, Hanser Susanne
Department of Medical Informatics, University Hospital Freiburg, Stefan Meier-Str. 26, D-79104 Freiburg, Germany.
AMIA Annu Symp Proc. 2007 Oct 11;2007:56-60.
The @neurIST ontology is currently under development within the scope of the European project @neurIST intended to serve as a module in a complex architecture aiming at providing a better understanding and management of intracranial aneurysms and subarachnoid hemorrhages. Due to the integrative structure of the project the ontology needs to represent entities from various disciplines on a large spatial and temporal scale. Initial term acquisition was performed by exploiting a database scaffold, literature analysis and communications with domain experts. The ontology design is based on the DOLCE upper ontology and other existing domain ontologies were linked or partly included whenever appropriate (e.g., the FMA for anatomical entities and the UMLS for definitions and lexical information). About 2300 predominantly medical entities were represented but also a multitude of biomolecular, epidemiological, and hemodynamic entities. The usage of the ontology in the project comprises terminological control, text mining, annotation, and data mediation.
@neurIST本体目前正在欧洲@neurIST项目范围内进行开发,旨在作为一个复杂架构中的模块,以更好地理解和管理颅内动脉瘤及蛛网膜下腔出血。由于该项目的整合结构,该本体需要在较大的空间和时间尺度上表示来自各个学科的实体。最初的术语获取是通过利用数据库框架、文献分析以及与领域专家的交流来进行的。本体设计基于DOLCE上层本体,并且在适当的时候链接或部分纳入其他现有的领域本体(例如,用于解剖实体的FMA和用于定义及词汇信息的UMLS)。该本体表示了约2300个主要为医学的实体,同时还包括大量生物分子、流行病学和血液动力学实体。该本体在项目中的用途包括术语控制、文本挖掘、注释和数据调解。