Computer-Aided Classification of Chronic Bronchitis in Comparison with Other Diagnostic Tools

  • R. Thurmayr
  • I. Schütz
  • R. Kaliebe
  • H. Schnieders
  • K. Karl
  • E. Fürnthaler
Conference paper
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 1)

Abstract

Under the sponsorship and in cooperation with the Bundesversicherungsanstalt für Angestellte (BfA) in Berlin and the Verband Deutscher Rentenversicherungsträger in Frankfurt, a method for computer-aided classification of severity grades for chronic bronchitis was developed. The purpose of classification into severity grades is to ease the assessment of chronic diseases together with their combinations and to make comparisons possible. This allows derivation of admission criteria for rehabilitational therapy which are suited to computerized processing. Using standardised severity grades permits better evaluation of the effectivity of in-patient care and monitoring the course and/or result of the treatment. Computer-aided determination of severity grades is also feasible in mass-screening programs of out-patient clinics, health services and health insurances as also in preventive care and epidemiological studies. The objective of this project was to reproduce by computer the severity grade estimation as made by a physician from symptoms characterising a clinical picture and to test this method on routine sample material.

Keywords

Europe Covariance Tempo Bronchitis Cough 

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References

  1. 1.
    Thurmayr, R., Schütz, I., Kaliebe, R., Computerunterstützte Bestimmung des Schweregrades bei der chronischen Bronchitis. in: Informationsverarbeitung in der Medizim - Wege und Irrwege. Bericht über die 22. Jahrestagung der GMDS EV. Göttingen. Ed.: Ehlers, C.Th., F.K. Schattauer-Verlag, Stuttgart-New York 1977 (in Press).Google Scholar
  2. 2.
    Kuntz, E.: Chronische Bronchitis. MMW Taschenbuch. J.F. Lehmanns-Verlag, München 19 75Google Scholar
  3. 3.
    Jelke, G., Möller, R., Schmidt, K.: Obstruktuve Atemwegserkrankungen (Teil 2: Stadieneinteilung der chronischen Bronchitis und Therapie). Med.Klin. 70, 1883–1887 (1975)PubMedGoogle Scholar
  4. 4.
    Lende, R. van der, Hansen-Koster, E.J., Knijpstra, S., Meinesz, A. Wever, A.M.J., Orie, N.G.M.: Definition of CNSLD: Use in epidemiology and preventive medicine. Selected Papers 17, 83 (1977)Google Scholar
  5. 5.
    Lange, H.-J. and R. Reiter: DFG-Forschungsbericht “Chronische Bronchitis”. Deutsche Forschungsgemeinschaft, Bonn-Bad Godesberg (1975)Google Scholar
  6. 6.
    Wolf, H.H.: STADAB, Statistisches Datenbank-Auswertungssystem. Statistical Software Newsletter 1, 63–66 (1975)Google Scholar
  7. 7.
    Fischbach, F, Groß, J., Ott, W.: Entscheidungstabellen. Verlagsgesellschaft Rudolf Müller, Köln-Braunsfeld, 1975, ISBN 3-481-32711-0Google Scholar
  8. 8.
    Veinott, G.C.: Programming Decision Tables in Fortran, Cobol or Algol, in: Communications of the ACM, Vol. 9Google Scholar
  9. 9.
    Victor, N., Hörmann, A., Eder, L.: STATSYS-Beschreibung und Benutzerahleitung. GSF Bericht, MD 24, München (1973)Google Scholar
  10. 10.
    Thurmayr, R., Kaliebe, R., Schnieders, H. Computer-aided classification of chronic bronchitis. AWAMI Annals of Wami Quarterly Journal 1978 (in press)Google Scholar
  11. 11.
    Lachenbruch, P.A.: Some Misuses of Discriminant Analysis. Meth.Inform.Med. 16, 255–258 (1977)PubMedGoogle Scholar
  12. 12.
    Thurmayr, R., Blomer, R.J. Computer aided diagnosis of pancreatic function tests in the routine situation. in: Decision making and medical care (Eds. by de Dombal and Gremy), North-Holland Publishing Company Amsterdam - New York - Oxford, 175–182 (1976)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1978

Authors and Affiliations

  • R. Thurmayr
    • 1
  • I. Schütz
    • 2
  • R. Kaliebe
    • 3
  • H. Schnieders
    • 3
  • K. Karl
    • 3
  • E. Fürnthaler
    • 3
  1. 1.Institut für Medizinische Statistik und EpidemiologieTU MünchenMünchen 80Deutschland
  2. 2.Werra-Klinik der BfABad Sooden-AllendorfDeutschland
  3. 3.Institut für Medizinische DatenverarbeitungGesellschaft für Strahlen- und Umweltforschung mbHMünchen 81Germany

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