Methods Inf Med 1995; 34(01/02): 147-157
DOI: 10.1055/s-0038-1634569
Original article
Schattauer GmbH

A Terminology Server for Medical Language and Medical Information Systems

A. L. Rector
1   Medical Informatics Group, Department of Computer Science, University of Manchester, Manchester, UK
,
W. D. Solomon
1   Medical Informatics Group, Department of Computer Science, University of Manchester, Manchester, UK
,
W. A. Nowlan
2   Medical Products Group, Hewlett-Packard Ltd., Bristol, UK
,
T. W. Rush
2   Medical Products Group, Hewlett-Packard Ltd., Bristol, UK
,
P. E. Zanstra
3   Department of Medical Informatics, University of Nymegen, The Netherlands
,
W. M. A. Claassen
3   Department of Medical Informatics, University of Nymegen, The Netherlands
› Author Affiliations
Further Information

Publication History

Publication Date:
09 February 2018 (online)

Abstract:

GALEN is developing a Terminology Server to support the development and integration of clinical systems through a range of key terminological services, built around a language-independent, re-usable, shared system of concepts – the CORE model. The focus is on supporting applications for medical records, clinical user interfaces and clinical information systems, but also includes systems for natural language understanding, clinical decision support, management of coding and classification schemes, and bibliographic retrieval. The Terminology Server integrates three modules: the Concept Module which implements the GRAIL formalism and manages the internal representation of concept entities, the Multilingual Module which manages the mapping of concept entities to natural language, and the Code Conversion Module which manages the mapping of concept entities to and from existing coding and classification schemes. The Terminology Server also provides external referencing to concept entities, coercion between data types, and makes its services available through a uniform applications programming interface. Taken together these services represent a new approach to the development of clinical systems and the sharing of medical knowledge.

 
  • References

  • 1 Lindberg D, Humphreys B, McCray A. The Unified Medical Language System. In: van Bemmel J. ed. 1993 Yearbook of Medical Informatics. Stuttgart: Schattauer Verlag; 1993: 41-53.
  • 2 Côté R, Rothwell D. SNOMED-3. Chicago: College of American Pathologists; 1993
  • 3 Read J. The Read Clinical Classification. NHS Centre for Coding and Classification; Loughborough, UK: 1993
  • 4 Evans DA, Cimino J, Hersh WR, Huff SM, Bell DS. The Canon Group. Position Statement: Towards a Medical Concept Representation Language. J Amer Med Inform Assoc 1994; 1: 207-17.
  • 5 Cimino JC, Hripscak G, Johnson S. Knowledge-based approaches to the maintenance of a large controlled medical terminology. J Amer Med Inform Assoc 1994; 1: 35-50.
  • 6 Rector A, Nowlan W, Glowinski A. Goals for concept representation in the GALEN project. In: 17th Annual Symposium on Computer Applications in Medical Care. New York: McGraw-Hill; 1993
  • 7 Rector A, Nowlan W, Kay S. Conceptual knowledge: the core of medical information systems. In: Lun K, Degoulet P, Rienhoff O. eds. Seventh World Congress on Medical Informatics, MEDINFO-92. Geneva: North Holland Publ; 1991: 1420-6.
  • 8 Rector A. Marking up is not enough. Meth Inform Med 1993; 32: 272-3.
  • 9 Lenat DB, Guha RV, Pittman K, Pratt D, Shepherd M. Cyc: toward programs with common sense. Comm ACM 1990; 33: 30-49.
  • 10 Lenat RGaDB. Re: CycLing paper reviews. Artif Intell 1993; 61: 149-74.
  • 11 McGuire JG, Kuokka D, Weber JC, Tenenbaum JM, Gruber TR, Olsen GR. SHADE: Technology for knowledge based collaborative engineering. J Concurrent Engin: Applic Res (CERA) 1993; 1: 1-17.
  • 12 Neches R, Fikes R, Finin T. et al. Enabling technology for knowledge sharing. AI Magazine 1991; 37-54.
  • 13 Patil RS, Fikes RE, Patel-Schneider PF. et al. The DARPA Knowledge Sharing Effort: Progress Report. Principles of Knowledge Representation and Reasoning, Third International Conference. Cambridge, MA: Morgan Kaufman; 1992
  • 14 Musen M. Dimensions of knowledge sharing and reuse. Comput Biomed Res 1992; 25: 435-67.
  • 15 Walther E, Eriksson H, Musen MA. Plugand-Play: Construction of task-specific expert-system shells using sharable context ontologies. AAAI Workshop on Knowledge Representation Aspects of Knowledge Acquision. San Jose, CA: AAAI Menlo Park CA; 1992: 191-8.
  • 16 Schreiber A, van Heijst G, Lanzola G, Stefanelli M. Knowledge organisation in medical KBS construction. In: Andreassen S, Engelbrecht P, Wyatt J. eds. Fourth Conference on Artificial Intelligence in Medicine Europe. Amsterdam: IOS Press; 1993: 394-405.
  • 17 Masarielr Jr F, Miller R, Bouhaddou O, Giuse N, Warner H. An interlingua for electronic interchange of medical information: using frames to map between clinical vocabularies. Comput Biomed Res 1991; 24: 379-400.
  • 18 Rector A, Nowlan W. The GALEN Representation and Integration Language (GRAIL) Kernel, Version 1. In: The GALEN Consortium for the EC AIM Programme. Available from Medical Informa_tics Group, University of Manchester; 1993
  • 19 Rector AL, Nowlan W. A Reusable Application Independent Model of Medical Terminology: GALEN’s GRAIL. KR-94. Berlin: Morgan Kaufmann; 1994
  • 20 Brachman RJ, McGuinness DL, Patel-Schneider PF, Resnick LA, Borgida A. Living with Classic: When and how to Use a KL-ONE-like language. In: Sowa J. ed. Principles of Semantic Networks: Explorations in the Representation of Knowledge. San Mateo, CA: Morgan Kaufmann; 1991: 401-56.
  • 21 Sowa J. Conceptual Structures: Knowledge Representation in Mind and Machine. New York: John Wiley & Sons; 1985
  • 22 Brachman R, Fikes R, Levesque H. An essential hybrid reasoning system; knowledge and symbol level accounts of KRYPTON. In: International Joint Conference on Artificial Intelligence (IJCAI-85). Morgan Kaufman; 1985: 532-9.
  • 23 World Health Organisation. International Classification of Diseases. Geneva: World Health Organisation; 1989
  • 24 Fikes R, Cutkosky M, Gruber T, Ballen JV. Knowledge Sharing Technology – Project Overview. Stanford University, Knowledge Sharing Laboratory; 1991
  • 25 Lenat DB, Guha RV. Building Large Knowledge-Based Systems: Representations and Inference in the Cyc Project. Reading, MA: Addison-Wesley; 1989: 372.
  • 26 Lenat D, Guha R. Ideas for applying Cyc. MCC; 1991
  • 27 Guha R, Lenat D. Cyc: a midterm report. AI Magazine 1990; 11: 32-59.