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Methods Inf Med 1995; 34(05): 511-517
DOI: 10.1055/s-0038-1634625
Original Article
Schattauer GmbH

Methodology for the Construction of a Disease Nomenclature and Classification System for Clinical Use

T. Kiuchil
1   Department of Epidemiology and Biostatistics, Faculty of Medicine, University of Tokyo, Japan
,
Y. Ohashi
1   Department of Epidemiology and Biostatistics, Faculty of Medicine, University of Tokyo, Japan
,
H. Sato
2   Department of Health Policy and Planning, Graduate School of International Health, Faculty of Medicine, University of Tokyo, Japan
,
S. Kaihara
3   Hospital Computer Center, University of Tokyo Hospital, Tokyo, Japan
› Author Affiliations
Further Information

Publication History

Publication Date:
17 February 2018 (online)

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Abstract:

The nature and problems of the linguistic representation of clinical data are discussed, using the linguistic theory of Ferdinand de Saussure. Based on the conclusions, a methodology for the construction of a disease nomenclature and a classification system, suitable for use in clinical information systems, is developed using set theory.

Keywords:

Linguistics - Nomenclature - Clinical information system - Set theory
 

  • References

  • 1 Van der Lei J, Musen M. Use and abuse of computer-stored medical data. Meth Inform Med 1991; 30: 79-80.
    PubMedGoogle Scholar
  • 2 Musen MA. The strained quality of medical data. Meth Inform Med 1989; 28: 123-5.
    PubMedGoogle Scholar
  • 3 Feinstein AR. ICD, POR, and DRG. Unsolved scientific problems in the nosology of clinical medicine. Arch Intern Med 1988; 148: 2269-74.
    CrossrefPubMedGoogle Scholar
  • 4 De Saussure F. Cours de Linguistique General. Paris: Payot; 1966
    Google Scholar
  • 5 Kiuchi T, Kaihara S. Machine translation and medical linguistics. In: Lun KC, Degoulet P, Piemme TE, Rienhoff O. eds. MEDINFO 92. Amsterdam: North-Holland; 1992: 1350-5.
    Google Scholar
  • 6 Cimino JJ, Barnett GO. Automated knowledge acquisition from MEDLINE. Meth Inform Med 1993; 32: 120-30.
    PubMedGoogle Scholar
  • 7 Ranum DL. Knowledge-based understanding of radiology text. Comput Meth Prog Biomed 1989; 30: 209-15.
    CrossrefPubMedGoogle Scholar
  • 8 Sager N, Freedman C, Lyman MS. eds. Medical Language Processing – Computer Management of Narrative Data. Reading: Addison-Wesley; 1987
    Google Scholar
  • 9 Mayer PS, Bailey GH, Mayer RJ, Hillis A, Dvoracek JE. Locative inferences in medical texts. J Med Syst 1987; 11: 123-35.
    CrossrefPubMedGoogle Scholar
  • 10 Baud RH, Rassinoux AM, Scherrer JR. Natural language processing and semantic representation of medical texts. Meth Inform Med 1992; 31: 117-25.
    PubMedGoogle Scholar
  • 11 Rasmussen JE, Bassoe CF. Semantic analysis of medical records. Meth Inform Med 1993; 32: 66-72.
    PubMedGoogle Scholar
  • 12 Zingmond D, Lenert LA. Monitoring freetext data using medical language processing. Comput Biomed Res 1993; 26: 467-81.
    CrossrefPubMedGoogle Scholar
  • 13 Kuhn K, Gauss W, Wechsler JG. et al. Structured reporting of medical findings: evaluation of a system in gastroenterology. Meth Inform Med 1992; 31: 268-74.
    PubMedGoogle Scholar
  • 14 Moorman PW, van Ginneken AM, van der Lei J, van Bemmel JH. A model for structured data entry basedon explicit descriptional knowledge. Meth Inform Med 1994; 33: 454-63.
    PubMedGoogle Scholar
  • 15 Dunham GS, Henson DE, Pacak MG. Three solutions to problems of categorized medical nomenclatures. Meth Inform Med 1984; 23: 87-95.
    PubMedGoogle Scholar