Literature DB >> 8563301

A multi-lingual architecture for building a normalised conceptual representation from medical language.

P Zweigenbaum1, B Bachimont, J Bouaud, J Charlet, J F Boisvieux.   

Abstract

The overall goal of MENELAS is to provide better access to the information contained in natural language patient discharge summaries (PDSs), through the design and implementation of a prototype able to analyse medical texts. The approach taken by MENELAS is based on the following key principles: (i) to maximise the usefulness of natural language analysis and the usability of its results, the output of natural language analysis must be a normalised conceptual representation of medical information; and (ii) to maximise the reuse of resources, language analysis should be domain-independent and conceptual representation should be language-independent. This paper discusses the results obtained and the issues raised when implementing these principles during the project.

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Year:  1995        PMID: 8563301      PMCID: PMC2579114     

Source DB:  PubMed          Journal:  Proc Annu Symp Comput Appl Med Care        ISSN: 0195-4210


  4 in total

1.  Dutch medical language processing: discussion of a prototype.

Authors:  P Spyns; J L Willems
Journal:  Medinfo       Date:  1995

2.  Effective retrieval in Hospital Information Systems: the use of context in answering queries to Patient Discharge Summaries.

Authors:  B Nangle; M T Keane
Journal:  Artif Intell Med       Date:  1994-06       Impact factor: 5.326

3.  MENELAS: an access system for medical records using natural language.

Authors:  P Zweigenbaum
Journal:  Comput Methods Programs Biomed       Date:  1994-10       Impact factor: 5.428

4.  Structuration and acquisition of medical knowledge. Using UMLS in the conceptual graph formalism.

Authors:  F Volot; P Zweigenbaum; B Bachimont; M Ben Said; J Bouaud; M Fieschi; J F Boisvieux
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1993
  4 in total
  5 in total

1.  Hospitexte: towards a document-based hypertextual electronic medical record.

Authors:  J Charlet; B Bachimont; V Brunie; S el Kassar; P Zweigenbaum; J F Boisvieux
Journal:  Proc AMIA Symp       Date:  1998

2.  Representing information in patient reports using natural language processing and the extensible markup language.

Authors:  C Friedman; G Hripcsak; L Shagina; H Liu
Journal:  J Am Med Inform Assoc       Date:  1999 Jan-Feb       Impact factor: 4.497

3.  Tumor information extraction in radiology reports for hepatocellular carcinoma patients.

Authors:  Wen-Wai Yim; Tyler Denman; Sharon W Kwan; Meliha Yetisgen
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2016-07-20

4.  Mining clinical relationships from patient narratives.

Authors:  Angus Roberts; Robert Gaizauskas; Mark Hepple; Yikun Guo
Journal:  BMC Bioinformatics       Date:  2008-11-19       Impact factor: 3.169

5.  Towards Converting Clinical Phrases into SNOMED CT Expressions.

Authors:  Rohit J Kate
Journal:  Biomed Inform Insights       Date:  2013-06-24
  5 in total

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