Literature DB >> 10566333

Model-based semantic dictionaries for medical language understanding.

A M Rassinoux1, R H Baud, P Ruch, B Trombert-Paviot, J M Rodrigues.   

Abstract

Semantic dictionaries are emerging as a major cornerstone towards achieving sound natural language understanding. Indeed, they constitute the main bridge between words and conceptual entities that reflect their meanings. Nowadays, more and more wide-coverage lexical dictionaries are electronically available in the public domain. However, associating a semantic content with lexical entries is not a straightforward task as it is subordinate to the existence of a fine-grained concept model of the treated domain. This paper presents the benefits and pitfalls in building and maintaining multilingual dictionaries, the semantics of which is directly established on an existing concept model. Concrete cases, handled through the GALEN-IN-USE project, illustrate the use of such semantic dictionaries for the analysis and generation of multilingual surgical procedures.

Mesh:

Year:  1999        PMID: 10566333      PMCID: PMC2232654     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  5 in total

1.  Acquisition of lexical resources from SNOMED for medical language processing.

Authors:  P Zweigenbaum; P Courtois
Journal:  Stud Health Technol Inform       Date:  1998

2.  Versatility of a multilingual and bi-directional approach for medical language processing.

Authors:  A M Rassinoux; C Lovis; R H Baud; J R Scherrer
Journal:  Proc AMIA Symp       Date:  1998

3.  Corpus-based identification and refinement of semantic classes.

Authors:  A Nazarenko; P Zweigenbaum; J Bouaud; B Habert
Journal:  Proc AMIA Annu Fall Symp       Date:  1997

4.  The content coverage of clinical classifications. For The Computer-Based Patient Record Institute's Work Group on Codes & Structures.

Authors:  C G Chute; S P Cohn; K E Campbell; D E Oliver; J R Campbell
Journal:  J Am Med Inform Assoc       Date:  1996 May-Jun       Impact factor: 4.497

5.  The use of morphosemantic regularities in the medical vocabulary for automatic lexical coding.

Authors:  S Wolff
Journal:  Methods Inf Med       Date:  1984-10       Impact factor: 2.176

  5 in total
  1 in total

1.  Automatic medical encoding with SNOMED categories.

Authors:  Patrick Ruch; Julien Gobeill; Christian Lovis; Antoine Geissbühler
Journal:  BMC Med Inform Decis Mak       Date:  2008-10-27       Impact factor: 2.796

  1 in total

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