Design of a Well-Protected Patient Record Unit for Multi-centre Knowledge-Based System CLINAID

  • Viswanathan Kaliappan
  • Ladislav J. Kohout
  • John Anderson
Conference paper
Part of the Lecture Notes in Medical Informatics book series (LNMED, volume 45)


In this paper, we describe the high level design of a general, modular and comprehensive Patient record unit (PRU) that can interface with two distinct environments simultaneously and provide for their mutual secure local or remote interaction. One environment is formed by a community of distributed interacting expert systems, or a multicentre concurrent Knowledge-Based System (KBS). The other environment consists of a community of data bases distributed locally or connected via a remote communication network. The paper is concluded with the description of the way in which the PRU is integrated within a multicentre, multi-context and multi-environment KBS CLinaid. Further relevant references to this approach are provided.


Human User Knowledge User Abstract Data Type Activity Graph High Level Design 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Brodie, M.L. and Myopulos, J. (eds.). On Knowledge Base Management Systems. Springer, Berlin, New York, 1986.MATHGoogle Scholar
  2. 2.
    Delacambre, L.M.L. and Etheredge, J.N. The relational production language: A production language for relational databases. In Kerschberg, L., editor, Expert Database Systems, pages 333–351, Benjamin Cummings, Redwood City, Calif., 1989.Google Scholar
  3. 3.
    Kohout, L.J., Anderson, J., and Bandler, W. Knowledge-Based Systems for Multiple Environments. Gower, Aldershot, U.K., 1991.Google Scholar
  4. 4.
    Kohout, L.J. A Perspective on Intelligent Systems: A Framework for Analysis and Design. Chapman and Hall & Van Nostrand, London & New York, 1990.MATHGoogle Scholar
  5. 5.
    Kohout, L.J. and Bandler, W. Computer Security Systems: Fuzzy Logics. In Singh, M.G., editor, Systems and Control Encyclopedia, Pergamon Press, Oxford, 1987.Google Scholar
  6. 6.
    Bandler, W. and Kohout, L.J. Mathematical relations. Ibid, pages 4000–4008.Google Scholar
  7. 7.
    Bandler, W. and Kohout, L.J. A survey of fuzzy relational products in their applicability to medicine and clinical psychology. In Kohout, L.J. and Bandler, W., editors, Knowledge Representation in Medicine and Clinical Behavioural Science, pages 107–118, an Abacus Book, Gordon and Breach Publ., London and New York, 1986.Google Scholar
  8. 8.
    Kohout, L.J., Anderson, J., Bandler, W., Gao, S., and Trayner, C. CLINAID: A knowledge- based system for support of decisions in the conditions of risk and uncertainty. In [3], chapter 10.Google Scholar
  9. 9.
    Kohout, L.J. and Bandler, W. The use of fuzzy information retrieval techniques in construction of multi-centre knowledge-based systems. In Bouchon, B. and Yager, R.R., editors, Uncertainty in Knowledge-Based Systems (Lecture Notes in Computer Science vol. 286) pages 257–264, Springer Verlag, Berlin, 1987.Google Scholar
  10. 10.
    Bandler, W. and Kohout, L.J. Fuzzy power sets and fuzzy implication operators. Fuzzy Sets and Systems, 4: 13–30, 1980.MathSciNetMATHCrossRefGoogle Scholar
  11. 11.
    Kohout, L.J., Bandler, W., Anderson, J., and Trayner, C. Knowledge-based decision support system for use in medicine. In Mitra, G., editor, Computer Models for Decision Making, pages 133–146, North-Holland, Amsterdam, 1985.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • Viswanathan Kaliappan
    • 1
  • Ladislav J. Kohout
    • 1
  • John Anderson
    • 2
  1. 1.The Center for Expert Systems and Robotics, Department of Computer ScienceFlorida State UniversityTallahasseeUSA
  2. 2.King’s College School of Medicine and DentistryUniversity of LondonUK

Personalised recommendations