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盖伦:一种支持外科手术多用途国家编码系统的第三代术语工具。

Galen: a third generation terminology tool to support a multipurpose national coding system for surgical procedures.

作者信息

Trombert-Paviot B, Rodrigues J M, Rogers J E, Baud R, van der Haring E, Rassinoux A M, Abrial V, Clavel L, Idir H

机构信息

Department of Public Health and Medical Informatics, Fac de Médecine, University of Saint Etienne, France.

出版信息

Stud Health Technol Inform. 1999;68:901-5.

Abstract

GALEN has developed a new generation of terminology tools based on a language independent concept reference model using a compositional formalism allowing computer processing and multiple reuses. During the 4th framework program project Galen-In-Use we applied the modelling and the tools to the development of a new multipurpose coding system for surgical procedures (CCAM) in France. On one hand we contributed to a language independent knowledge repository for multicultural Europe. On the other hand we support the traditional process for creating a new coding system in medicine which is very much labour consuming by artificial intelligence tools using a medically oriented recursive ontology and natural language processing. We used an integrated software named CLAW to process French professional medical language rubrics produced by the national colleges of surgeons into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation on one hand we generate controlled French natural language to support the finalization of the linguistic labels in relation with the meanings of the conceptual system structure. On the other hand the classification manager of third generation proves to be very powerful to retrieve the initial professional rubrics with different categories of concepts within a semantic network.

摘要

盖伦基于一种独立于语言的概念参考模型开发了新一代术语工具,该模型使用组合形式主义,允许计算机处理和多次复用。在第四个框架计划项目“实际应用中的盖伦”中,我们将该建模和工具应用于法国一种新的外科手术多用途编码系统(CCAM)的开发。一方面,我们为多元文化的欧洲建立了一个独立于语言的知识库。另一方面,我们支持医学中创建新编码系统的传统流程,该流程通过使用面向医学的递归本体和自然语言处理的人工智能工具,非常耗费人力。我们使用一个名为CLAW的集成软件,将法国外科医生国家学院生成的法语专业医学语言条目处理成中间解剖结构,并转化为圣杯参考本体模型表示。从这个独立于语言的概念模型表示出发,一方面,我们生成受控的法语自然语言,以支持根据概念系统结构的含义确定语言标签的最终形式。另一方面,事实证明,第三代分类管理器在语义网络中检索具有不同概念类别的初始专业条目时非常强大。

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