title: Automatic extraction of linguistic knowledge from an international classification.
abstract: Automatic extraction of knowledge from large corpus of texts is an essential step toward linguistic knowledge acquisition in the medical domain. The current situation shows a lack of computer-readable large medical lexicons, with a partial exception for the English language. Moreover, multilingual lexicons with versatility for multiple languages applications are far from reach as long as only manual extraction is considered. Computer-assisted linguistic knowledge acquisition is a must. A multilingual lexicon differs from a monolingual one by the necessity to bridge the words in different languages. A kind of interlingua has to be built under the form of concepts to which the specific entries are attached. In the present approach, the authors have developed an intelligent rule-based tool in order to focus on a multilingual source of medical knowledge, like the International Classification of Disease (ICD) which contains a vocabulary of some 20,000 words, translated in numerous languages.
authors.affiliation: Division d'Informatique Médicale, University Hospital of Geneva, Switzerland. Robert.Baud@dim.hcuge.ch
authors.forename: R
authors.initials: R
authors.lastname: Baud
authors.forename: C
authors.initials: C
authors.lastname: Lovis
authors.forename: A M
authors.initials: AM
authors.lastname: Rassinoux
authors.forename: P A
authors.initials: PA
authors.lastname: Michel
authors.forename: J R
authors.initials: JR
authors.lastname: Scherrer
mesh_terms: D004194:Disease / Q000145:classification; D005103:Expert Systems; D006801:Humans; D016247:Information Storage and Retrieval; D019303:Multilingualism; D009323:Natural Language Processing; D018875:Vocabulary, Controlled