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Methods Inf Med 1998; 37(01): 86-96
DOI: 10.1055/s-0038-1634504
Original Article
Schattauer GmbH

Review of Biomedical Knowledge and Data Representation with Conceptual Graphs

F. Volot
1   Service de l’Information Médicale, Hôpital de la Timone Aduites, Assistance Publique-Hôpitaux de Marseille
,
M. Joubert
1   Service de l’Information Médicale, Hôpital de la Timone Aduites, Assistance Publique-Hôpitaux de Marseille
2   Centre d’Enseignement et de Recherche en Traitement de l’Information Médicale, Faculté de Médecine de Marseille, Université de la Méditerranée, France
,
M. Fieschi
1   Service de l’Information Médicale, Hôpital de la Timone Aduites, Assistance Publique-Hôpitaux de Marseille
2   Centre d’Enseignement et de Recherche en Traitement de l’Information Médicale, Faculté de Médecine de Marseille, Université de la Méditerranée, France
› Author Affiliations
Further Information

Publication History

Publication Date:
07 February 2018 (online)

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Abstract:

The basis of conceptual graphs theory is an ontology of types of concepts. Concepts issued from the ontology are interlinked by semantic relationships and constitute canonical conceptual graphs. Canonical graphs may be combined to derive new conceptual graphs by means of formation rules. This formalism allows to separate knowledge representation into a conceptual level and a domain-dependent level, and enables to share and reuse a representation. This paper presents conceptual graph applications to biomedical data and concept representation, classification systems, information retrieval, and natural language understanding and processing. A discussion on the unifying role conceptual graphs theory plays in the implementation of knowledge-based systems is also presented.

Keywords

Knowledge Representation - Conceptual Graphs - Information Processing - Classification Systems - Information Retrieval - Natural Language Processing
 

  • REFERENCES

  • 1 Sowa JF. Conceptual Structures: Information Processing in Mind and Machine. Addison Wesley; 1984
    Google Scholar
  • 2 Sowa JF. Conceptual graphs as a universal knowledge representation. Comput Math App 1992; 23: 75-93.
    PubMedGoogle Scholar
  • 3 Sowa JF. Conceptual analysis as a basis for knowledge representation. Meth Inform Med 1995; 34: 165-71.
    PubMedGoogle Scholar
  • 4 Bernauer J. Conceptual graphs as an operational model for descriptive findings. In: Frisse ME. ed. Sixteenth Symposium on Computer Applications in Medical Care. New York: McGraw Hill; 1992: 214-8.
    Google Scholar
  • 5 Campbell K, Das A, Musen M. A logical foundation for representation of clinical data. JAM IA 1994; 1: 218-32.
    PubMedGoogle Scholar
  • 6 Campbell K, Musen M. Representation of clinical data using SNOMED III and conceptual graphs. In: Frisse ME. ed. Sixteenth Symposium on Computer Applications in Medical Care. New York: McGraw Hill; 1992: 354-8.
    Google Scholar
  • 7 Campbell K, Wieckert K, Fagan L, Musen M. A computer-based tool for generation of progress notes. In: Safran C. ed. Seventeenth Symposium on Computer Applications in Medical Care. New York: McGraw Hill; 1993: 284-8.
    Google Scholar
  • 8 Bell DS, Pattison-Gordon E, Greenes RA. Experiments in concept modeling for radiographic image reports. JAMIA 1994; 1: 249-62.
    PubMedGoogle Scholar
  • 9 Friedman C, Cimino JJ, Johnson SB. A schema for representing medical language applied to clinical radiology. JAMIA 1994; 1: 233-48.
    PubMedGoogle Scholar
  • 10 Johnson SB. Generic data modeling for clinical repositories. JAMIA 1996; 3: 328-39.
    PubMedGoogle Scholar
  • 11 Bernauer J, Goldberg H. Compositional classification based on conceptual graphs. In: Andreassen et al eds. Artificial Intelligence in Medicine Europe. Amsterdam: IOS Press; 1993: 348-59.
    Google Scholar
  • 12 Bernauer J, Franz M, Schoop D, Schoop M, Pretschner DP. The compositional approach for representing medical concept systems. In: Greenes R, Peterson H, Protti D. eds. MEDINFO 95. Amsterdam: North-Holland; 1995: 70-4.
    Google Scholar
  • 13 Joubert M, Fieschi M, Robert JJ, Tafazoli AG. Conceptual users views on medical information databases. Int J Biomed Comput 1994; 37: 93-104.
    CrossrefPubMedGoogle Scholar
  • 14 Joubert M, Robert JJ, Miton F, Fieschi M. The project ARIANE: conceptual queries to information databases. In: Cimino J. ed. Proc. AMIA Annual Fall Symposium. JAMIA Symposium Supplement. 1996; 378-82.
    PubMedGoogle Scholar
  • 15 Zweigenbaum P. et al. MENELAS: An access system for medical records using natural language. Comput Meth Prog Biomed 1994; 45: 117-20.
    CrossrefPubMedGoogle Scholar
  • 16 Baud RH, Rassinoux AM, Wagner J. et al. Representing clinical narratives using conceptual graphs. Meth Inform Med 1995; 34: 176-86.
    PubMedGoogle Scholar
  • 17 Gruber TR. A translation approach to portable ontologies. Knowledge Acquisition 1993; 5: 199-220.
    CrossrefPubMedGoogle Scholar
  • 18 Lindberg DAB, Humphreys BL, McCray AT. The Unified Medical Language System. Meth Inform Med 1993; 32: 281-91.
    PubMedGoogle Scholar
  • 19 McCray AT, Nelson SJ. The Representation of Meaning in the UMLS. Meth Inform Med 1995; 34: 193-201.
    PubMedGoogle Scholar
  • 20 Tuttle MS, Olson NE, Campbell KE. et al. Formal properties of the Metathesaurus. In: Ozbolt JG. ed. Eighteenth Symposium on Computer Applications in Medical Care. JAMIA. 1994; symposium supplement 145-9.
    PubMedGoogle Scholar
  • 21 Volot F, Zweigenbaum P, Bachimont B. et al. Structuration and acquisition of medical knowledge using UMLS in the conceptual graph formalism. In: Safran C. ed. Seventeenth Symposium on Computer Applications in Medical Care. New York: MacGraw Hill; 1993: 710-4.
    Google Scholar
  • 22 Zweigenbaum P, Bachimont B, Bouaud J. et al. Issues in the structuring and acquisition of an ontology for medical language understanding. Meth Inform Med 1995; 34: 15-24.
    PubMedGoogle Scholar
  • 23 Rector AL, Solomon W, Nowlan W, Rush T. A terminology server for medical language and medical information systems. Meth Inform Med 1995; 34: 147-57.
    PubMedGoogle Scholar
  • 24 Rector AL, Rogers JE, Pole P. The GALEN high level ontology. In: Brender J, Christensen JP, Scherrer JR, McNair P. eds. Medical Informatics in Europe 96. Amsterdam: IOS Press; 1996: 174-8.
    Google Scholar
  • 25 Way E. Conceptual graphs – Past, present and future. In: Tepfenhart W, Dick J, Sowa J. eds. Conceptual structures: current practices. Lectures Notes in Artificial Intelligence 835. Berlin: Springer-Verlag; 1994: 17-29.
    Google Scholar
  • 26 Biebow B, Chaty G. A comparison between conceptual graphs and KL-one. In: Mineau G, Moulin B, Sowa JF. eds. Conceptual graphs for knowledge representation. Lecture Notes in Artificial Intelligence 699. Berlin: Springer-Verlag; 1993: 75-89.
    Google Scholar
  • 27 Willems M. A conceptual semantics ontology for conceptual graphs. In: Mineau G, Moulin B, Sowa JF. eds. Conceptual graphs for knowledge representation. Lecture Notes in Artificial Intelligence 699. Berlin: Springer-Verlag; 1993: 312-27.
    Google Scholar
  • 28 Chein M, Mugnier ML. Conceptual graphs: fundamental notions. La Revue d'lntelligence Artificielle 1992; 6: 365-406.
    PubMedGoogle Scholar
  • 29 Evans DA, Cimino JJ, Hersh WR. et al. for the CANON Group. Toward a medical-concept representation language. JAMIA 1994; 1: 218-32.
    PubMedGoogle Scholar
  • 30 Rossi Mori A, Gangemi A, Galanti M. The coding cage. In: Reichertz A, Sadan BA, Bengtsson S. et al. eds. Medical Informatics in Europe 93. London: Freund Publishing House; 1993: 466-72.
    Google Scholar
  • 31 Bernauer J. Subsumption principles underlying medical concept systems and their formal reconstruction. In: Ozbolt JG. ed. Eighteenth Symposium on Computer Applications in Medical Care. JAMIA. 1994; symposium supplement 140-4.
    PubMedGoogle Scholar
  • 32 Yang Y, Chute CG. A Schematic analysis of the Unified Medical Language System. In: Frisse ME. ed. Sixteenth Symposium on Computer Applications in Medical Care. New York: McGraw Hill; 1992: 204-8.
    Google Scholar
  • 33 Joubert M, Fieschi M, Robert JJ. A conceptual model for information retrieval with UMLS. In: Safran C. ed. Seventeenth Symposium on Computer Applications in Medical Care. New York: McGraw Hill; 1993: 715-9.
    Google Scholar
  • 34 Joubert M, Miton F, Fieschi M, Robert JJ. A conceptual graphs modelling of UMLS components. In: Greenes R, Peterson H, Protti D. eds. MEDINFO 95. Amsterdam: North-Holland; 1995: 90-4.
    Google Scholar
  • 35 Shastri L. Why Semantic Networks?. In: Sowa JF. ed. Principles of semantic networks: exploration in the representation of knowledge. Morgan Kaufmann; 1991: 109-36.
    Google Scholar
  • 36 Cimino JJ, Hripcsak G, Johnson SB. et al. UMLS as knowledge base – a rule-based expert system approach to controlled medical vocabulary management. In: Miller RA. ed. Fourteenth Symposium on Computer Applications in Medical Care. IEEE Computer Society Press; 1990: 175-84.
    Google Scholar
  • 37 Kirby J, Rector AL. The PEN&PAD Data Entry System: From prototype to practical system. In: Cimino J. ed. Proc. AMIA Annual Fall Symposium. JAMIA Symposium Supplement. 1996; 709-13.
    PubMedGoogle Scholar
  • 38 Moorman PW, van Ginneken AM, van der Lei J, van Bemmel JH. A model for structured data entry based on explicit descriptional knowledge. Meth Inform Med 1994; 33: 45463.
    PubMedGoogle Scholar
  • 39 Zweigenbaum P, Bachimont B, Bouaud J. et al. A multi-lingual architecture for building a normalised conceptual representation from medical language. In: Gardner RM. ed. Nineteenth Symposium on Computer Applications in Medical Care. JAMIA 1995; symposium supplement 357-61.
    PubMedGoogle Scholar
  • 40 Baud R, Lovis C, Alpay L. et al. A. Modelling for natural language understanding. In: Ozbolt JG. ed. Eighteenth Symposium on Computer Applications in Medical Care. JAMIA 1994; symposium supplement 28993.
    PubMedGoogle Scholar
  • 41 Rassinoux AM, Baud R, Scherrer JR. A multilingual analyser of medical texts. In: Tepfenhart W, Dick J, Sowa J. eds. Conceptual structures: current practices. Lectures Notes in Artificial Intelligence 835. Berlin: Springer-Verlag; 1994: 84-96.
    Google Scholar
  • 42 Baud R, Rassinoux AM, Scherrer JR. Knowledge representation of discharge summaries. In: Stefanelli M. et al. eds. Artificial Intelligence in Medicine Europe. Lecture Notes in Medical Informatics 44. Berlin: Springer-Verlag; 1991: 173-82.
    Google Scholar
  • 43 Alpay L, Baud R, Rassinoux AM. et al. Interfacing Conceptual Graphs (CG) and the Galen Master Notation (MN) for medical knowledge representation and modelling. In: Andreassen et al. eds. Artificial Intelligence in Medicine Europe. Amsterdam: IOS Press; 1993: 337-47.
    Google Scholar
  • 44 Wagner JC, Solomon WD, Michel PA. et al. Multilingual natural language generation as part of medical terminology server. In: Greenes R, Peterson H, Protti D. eds. MEDINFO 95. Amsterdam: North-Holland; 1995: 100-4.
    Google Scholar
  • 45 Ingeneri J. Taxonomic vocabularies in medicine: the intention of usage determines different established structures. In: Greenes R, Peterson H, Protti D. eds. MEDINFO 95. Amsterdam: North-Holland; 1995: 136-9.
    Google Scholar
  • 46 Musen MA. Dimensions of knowledge sharing and reuse. Comput Biomed Research 1992; 25: 437-67.
    PubMedGoogle Scholar
  • 47 Davis R, Shrobe H, Szolovits P. What is a knowledge representation?. Artificial Intelligence Magazine 1993; 14: 17-33.
    PubMedGoogle Scholar