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

Generalised architecture for languages, encyclopedia and nomenclatures in medicine (GALEN) has developed a new generation of terminology tools based on a language independent model describing the semantics and allowing computer processing and multiple reuses as well as natural language understanding systems applications to facilitate the sharing and maintaining of consistent medical knowledge. During the European Union 4 Th. framework program project GALEN-IN-USE and later on within two contracts with the national health authorities we applied the modelling and the tools to the development of a new multipurpose coding system for surgical procedures named CCAM in a minority language country, France. On one hand, we contributed to a language independent knowledge repository and multilingual semantic dictionaries 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 (for classification workbench) to process French professional medical language rubrics produced by the national colleges of surgeons domain experts into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation, on one hand, we generate with the LNAT natural language generator controlled French natural language to support the finalization of the linguistic labels (first generation) in relation with the meanings of the conceptual system structure. On the other hand, the Claw classification manager proves to be very powerful to retrieve the initial domain experts rubrics list with different categories of concepts (second generation) within a semantic structured representation (third generation) bridge to the electronic patient record detailed terminology.

Water vole (Arvicola terrestris scherman) density as risk factor for human alveolar echinococcosis.

Concern is growing in Europe about alveolar echinococcosis (AE) with the increase in grassland rodent and red fox populations, intermediate and definitive hosts for Echinococcus multilocularis, respectively. The objective of this study was to assess the influence of rodent densities on human AE distribution. Spatial Poisson regression analyses were performed with geomorphologic features, landscape composition, climatic characteristics, and water vole density as independent variables. The outcome consisted of AE cases diagnosed over the period 1980-1992. High vole density yielded a 10-fold risk (relative risk [RR] = 10.34, 95% confidence interval [CI] = 2.78-38.39), and the first plateau (400-700 m altitude) compared with the plain (200-400 m) was associated with a large increase in risk (RR = 7.10, 95% CI = 1.30-38.63). These results confirm that human AE is strongly influenced by the densities of arvicolid species. Foxes feeding almost exclusively on grassland rodents when the latter expand could mediate this relation.

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

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.