Abstract
In the medical field, it is now established that the maintenance of unambiguous thesauri is accomplished by the building of ontologies. Our task in the PertoMed project is to help pneumologists code acts and diagnoses with a software that represents medical knowledge by an ontology of the concerned specialty. We apply natural language processing tools to corpora to develop the resources needed to build this ontology. In this paper, our objective is to develop a methodology for the knowledge engineer to build various types of medical ontologies based on terminology extraction from texts according to the differential semantics theory. Our main research hypothesis concerns the joint use of two methods: distributional analysis and recognition of semantic relationships by lexico-syntactic patterns. The expected result is the building of an ontology of pneumology.
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Baneyx, A., Charlet, J., Jaulent, MC. (2005). Building Medical Ontologies Based on Terminology Extraction from Texts: Methodological Propositions. In: Miksch, S., Hunter, J., Keravnou, E.T. (eds) Artificial Intelligence in Medicine. AIME 2005. Lecture Notes in Computer Science(), vol 3581. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527770_33
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DOI: https://doi.org/10.1007/11527770_33
Publisher Name: Springer, Berlin, Heidelberg
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