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DOI: 10.1055/s-0038-1634546
Formal Classification of Medical Concept Descriptions: Graph-Oriented Operators
This work was funded in part hy the European GALEN-IN-USE project (HC 1018)Publikationsverlauf
Publikationsdatum:
15. Februar 2018 (online)
Abstract
A crucial component of a medical concept representation system is the classifier. It requires features that are not sufficiently supported by current logic based formalisms like description logics and conceptual graphs. Those features are, for instance, the representation of partitive and spatial relations and their impact on sUbsumption. This paper introduces graph oriented classification operators for a concept representation language with normal forms. Emphasis is on the separation of generic and partitive relations and on the mutual interdependence of sUbsumption and part-whole. For that purpose operators are given for formal subsumption, formal part-whole, subsumptive part-whole and part-sensitive subsumption. These operators are based on the formal structure of concept descriptions and on explicitly introduced generic and partitive relationships between their constituents.
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REFERENCES
- 1 Rector AL, Glowinski AJ, Nowlan WA, Rossi-Mori A. Medical-concept Models and Medical Records: An Approach Based on GALEN and PEN&PAD. J Am Med Informatics Assoc 1995; 2: 19-35.
- 2 Campbell KE, Das AK, Musen MA. A Logical Foundation for Representation of Clinical Data. J Am Med Informatics Assoc 1994; (1) 218-32.
- 3 Friedman C, Cimino JJ, Johnson SB. A schema for representing medical language applied to clinical radiology. J Am Med Informatics Assoc 1994; 1: 233-48.
- 4 Zweigenbaum P, Bachimont B, Bounaud J, Charlet J, Boisvieux JF. Issues in the Structuring and Acquisition of an Ontology for Medical Language Understanding. Meth Inform Med 1995; 34: 15-24.
- 5 Bernauer J. Conceptual graphs as an operational model for descriptive findings. In: Clayton PD. (ed.) Proceedings 15th Symposium on Computer Applications in Medical Care 1991. McGraw-Hill; 214-8.
- 6 Woods WA, Schmölze JG. The KL-ONE family. Comp Math AppI 1992; (23) 133-77.
- 7 Sowa JF. Conceptual Structures: Information Processing in Mind and Maschine. Addison-Wesley; 1984
- 8 Bernauer J. Analysis of part-whole relation and subsumption in the medical domain. Data Knowl Eng 1996; 20: 405-15.
- 9 Bernauer J. Subsumption principles underlying medical concept systems and their formal reconstruction. In: Ozbolt JG. (ed.) Proceedings 18th Annual Symposium on Computer Applications in Medical Care (SCAMC '94). Washington DC: 1994: 140-4.
- 10 Winston ME, Chaffin R, Herrmann D. A Taxonomy of Part-Whole Relations. Cog Sei 1987; 11: 417-44.
- 11 Gerstl P, Pribbenow S. A conceptual theory of part-whole relations and its application. Data Knowl Eng 1996; 20: 305-22.
- 12 Woods WA. Understanding Subsumption and Taxonomy: A Framework for Progress. In: Sowa JF. (ed.) Principles of Semantic Networks. San Mateo CA: Morgan Kaufmann Publishers; 1991: 45-94.
- 13 Schmölze JG, Mark WS. The NIKL experience. Comput Intell 1991; 7 (1) 48-69.
- 14 Doyle J, Patil RS. Two theses of knowledge representation: language restrictions, taxonomic classification, and the utility of representation services. Artificial Intelligence 1991; (48) 261-97.
- 15 Donini F, Lenzerini M, Nardi D, Nutt W. The complexity of concept languages. In: Allan JA, Fikes R, Sandewall E. (eds.) Proceedings of the Second International Conference On Principles of Knowledge Representation. Cambridge: 1991
- 16 Haimowitz IJ, Patil RS, Szolovits P. Representing medical knowledge in a terminological language is difficult. In: Greenes RA. (eds.) Proceedings 12th Symposium on Computer Applications in Medical Care 1988. IEEE Computer Society Press; 101-5.
- 17 Côté RA, Rothwell DJ. et al. The Systematized Nomenclature of Medicine: SNOMED International. Northfield, Illinois: Collge of American Pathologists; 1993