A knowledge-based modelling of hospital information systems components

  • Henry Kanoui
  • Michel Joubert
  • René Favard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 934)


In this paper, we point out the necessity for large information systems, and especially hospital information systems, to encompass a knowledge-based model of the domain covered. We discuss the characteristics of such a model and present the knowledge representation adopted in previous projects. The XQL formalism, which enables application programs to query the model at run-time, is then introduced. The theoretical model and operational semantics of XQL are presented and discussed.


Knowledge Representation Operational Semantic Semantic Network Hospital Information System Semantic Relationship 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Joubert M, Kanoui H. The knowledge-based management of medical acts in NUCLEUS. In: Andreassen S, Engelbrecht R, Wyatt J, (eds), Proc. AIME 93. IOS Press, 1993: 377–380.Google Scholar
  2. [2]
    Kanoui H, Joubert M, Riouall D, Favard R. Customisation environment for an act-based hospital information system. In: Reichert A, Sadan BA, Bengtsson S, Bryant J, Piccolo U (eds), Proc. MIE'93. Freund Publish. 1993: 241–245.Google Scholar
  3. [3]
    Kanoui H, Joubert M, Favard R. Knowledge-based model and query language to medical databases in a hospital information system. In: Barahona P, Veloso M, Bryant J, (eds), Proc. MIE'94. 1994: 379–383.Google Scholar
  4. [4]
    Brachman RJ, Schmolze JG. An overview of the KL-ONE knowledge representation system. Cognitive Science 9. 1985: 171–216.CrossRefGoogle Scholar
  5. [5]
    Brachman RJ, McGuinness DL, Patel-Schneider PF, Resnick LA, Bordiga A. Living with CLASSIC: when and how to use a KL-ONE-like language. In: Sowa JF (ed), Principles of semantic networks: exploration in the representation of knowledge. Morgan Kaufmann Publish. 1991: 401–456.Google Scholar
  6. [6]
    Woods WA. Understanding subsumption and taxonomy. In: Sowa JF (ed), Principles of semantic networks: exploration in the representation of knowledge. Morgan Kaufmann Publish. 1991: 45–94.Google Scholar
  7. [7]
    Sowa JF. Conceptual Structures: information processing in mind and machine. Addison Wesley, 1984.Google Scholar
  8. [8]
    Sowa JF. Conceptual analysis as a basis for knowledge representation. Tutorial Handbook. MEDINFO 92. 1992.Google Scholar
  9. [9]
    Chein M, Mugnier ML. Conceptual graphs: fundamental notions. Revue d'Intelligence Artificielle 6. 1992: 365–406.CrossRefGoogle Scholar
  10. [10]
    Volot F, Zweigenbaum P, Bachimont B, Ben Said M, Bouaud J, Fieschi M, Boisvieux JF. Structuration and acquisition of Medical knowledge using UMLS in the conceptual graphs formalism. In: Safran C (ed), Proc. 17th SCAMC. McGraw-Hill. 1993: 710–714.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Henry Kanoui
    • 1
  • Michel Joubert
    • 1
    • 2
  • René Favard
    • 1
  1. 1.Technopôle de Château-Gombert, Europarc, bat. CIIRIAMMarseille Cedex 13France
  2. 2.Faculté de MédecineCERTIMMarseille Cedex 15France

Personalised recommendations