Review of Biomedical Knowledge and Data Representation with Conceptual Graphs

F. Volot; M. Joubert; M. Fieschi

doi:10.1055/s-0038-1634504

Methods of Information in Medicine, Table of Contents

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

¹Service de l’Information Médicale, Hôpital de la Timone Aduites, Assistance Publique-Hôpitaux de Marseille

,

M. Joubert

¹Service de l’Information Médicale, Hôpital de la Timone Aduites, Assistance Publique-Hôpitaux de Marseille

²Centre d’Enseignement et de Recherche en Traitement de l’Information Médicale, Faculté de Médecine de Marseille, Université de la Méditerranée, France

,

M. Fieschi

¹Service de l’Information Médicale, Hôpital de la Timone Aduites, Assistance Publique-Hôpitaux de Marseille

²Centre d’Enseignement et de Recherche en Traitement de l’Information Médicale, Faculté de Médecine de Marseille, Université de la Méditerranée, France

› Author Affiliations

Abstract

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

Full Text

References

REFERENCES
1 Sowa JF. Conceptual Structures: Information Processing in Mind and Machine. Addison Wesley; 1984
2 Sowa JF. Conceptual graphs as a universal knowledge representation. Comput Math App 1992; 23: 75-93.
3 Sowa JF. Conceptual analysis as a basis for knowledge representation. Meth Inform Med 1995; 34: 165-71.
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.
5 Campbell K, Das A, Musen M. A logical foundation for representation of clinical data. JAM IA 1994; 1: 218-32.
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.
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.
8 Bell DS, Pattison-Gordon E, Greenes RA. Experiments in concept modeling for radiographic image reports. JAMIA 1994; 1: 249-62.
9 Friedman C, Cimino JJ, Johnson SB. A schema for representing medical language applied to clinical radiology. JAMIA 1994; 1: 233-48.
10 Johnson SB. Generic data modeling for clinical repositories. JAMIA 1996; 3: 328-39.
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.
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.
13 Joubert M, Fieschi M, Robert JJ, Tafazoli AG. Conceptual users views on medical information databases. Int J Biomed Comput 1994; 37: 93-104.
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.
15 Zweigenbaum P. et al. MENELAS: An access system for medical records using natural language. Comput Meth Prog Biomed 1994; 45: 117-20.
16 Baud RH, Rassinoux AM, Wagner J. et al. Representing clinical narratives using conceptual graphs. Meth Inform Med 1995; 34: 176-86.
17 Gruber TR. A translation approach to portable ontologies. Knowledge Acquisition 1993; 5: 199-220.
18 Lindberg DAB, Humphreys BL, McCray AT. The Unified Medical Language System. Meth Inform Med 1993; 32: 281-91.
19 McCray AT, Nelson SJ. The Representation of Meaning in the UMLS. Meth Inform Med 1995; 34: 193-201.
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.
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.
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.
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.
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.
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.
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.
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.
28 Chein M, Mugnier ML. Conceptual graphs: fundamental notions. La Revue d'lntelligence Artificielle 1992; 6: 365-406.
29 Evans DA, Cimino JJ, Hersh WR. et al. for the CANON Group. Toward a medical-concept representation language. JAMIA 1994; 1: 218-32.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
46 Musen MA. Dimensions of knowledge sharing and reuse. Comput Biomed Research 1992; 25: 437-67.
47 Davis R, Shrobe H, Szolovits P. What is a knowledge representation?. Artificial Intelligence Magazine 1993; 14: 17-33.