Rodrigues J M, Trombert-Paviot B, Baud R, Wagner J, Meusnier-Carriot F
Department of Public Health and Medical Informatics University of Saint Etienne Jean Monnet, France.
Stud Health Technol Inform. 1998;52 Pt 1:623-7.
GALEN has developed a language independent common reference model based on a medically oriented ontology and practical tools and techniques for managing healthcare terminology including natural language processing. GALEN-IN-USE is the current phase which applied the modelling and the tools to the development or the updating of coding systems for surgical procedures in different national coding centers co-operating within the European Federation of Coding Centre (EFCC) to create a language independent knowledge repository for multicultural Europe. We used an integrated set of artificial intelligence terminology tools named CLAssification Manager workbench to process French professional medical language rubrics into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation we generate controlled French natural language. The French national coding centre is then able to retrieve the initial professional rubrics with different categories of concepts, to compare the professional language proposed by expert clinicians to the French generated controlled vocabulary and to finalize the linguistic labels of the coding system in relation with the meanings of the conceptual system structure.
盖伦基于医学导向的本体论以及包括自然语言处理在内的医疗术语管理实用工具和技术，开发了一种与语言无关的通用参考模型。“实际应用中的盖伦”是当前阶段，该阶段将建模和工具应用于不同国家编码中心外科手术编码系统的开发或更新，这些编码中心在欧洲编码中心联合会（EFCC）内合作，为多元文化的欧洲创建一个与语言无关的知识库。我们使用了一组名为分类管理器工作台的人工智能术语工具，将法语专业医学语言条目处理为中间解剖结构，并转化为圣杯参考本体模型表示。从这种与语言无关的概念模型表示中，我们生成受控的法语自然语言。然后，法国国家编码中心能够检索带有不同概念类别的初始专业条目，将专家临床医生提出的专业语言与生成的法语受控词汇进行比较，并根据概念系统结构的含义确定编码系统的语言标签。
