Dynamic propagation in causal probabilistic networks with instantiated variables

  • O. K. Hejlesen
  • S. Andreassen
  • S. K. Andersen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 934)


An extension to the Hugin tool for implementing dynamic propagation in causal probabilistic networks with some instantiated variables is presented. The extension makes it possible to combine a dynamically defined network, implemented without the use of Hugin, with a static network implemented in Hugin, thereby reducing the calculation time by several orders of magnitude compared to using Hugin alone. The application of the dynamic propagation in a Diabetes Advisory System, DIAS, for giving advise on insulin dose adjustment in insulin dependent diabetes mellitus, is described as an example.


Time Slice Static Part Insulin Injection Dynamic Propagation Dynamic Part 
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).
    Andersen, S.K., Olesen, K.G., Jensen, F.V., and Jensen, F., 1991. HUGIN — A shell for building Bayesian belief universes for exper systems. In: Proceedings of IJCAI 89 2, pp. 1080–1085.Google Scholar
  2. 2).
    Andreassen, S., Jensen, F.V., Andersen, S.K., Falck, B., Kjærulff, U., Woldbye, M., Sørensen, A.R., Rosenfalck, A., and Jensen F. 1989. MUNIN — An expert EMG assistant. Computer-Aided Electromyography and Expert Systems, (ed. Desmedt, J. E.) Elsevier, pp 255–277.Google Scholar
  3. 3).
    Andreassen, S., Hovorka, R., Benn, J., Olesen, K.G., and Carson, E., 1991. A model-based approach to insulin adjustment. In: Lecture Notes in Medical Informatics, (eds. M. Stefanelli, A. Hasman, M. Fieschi, and J. Talmon), vol. 44, pp 239–249, Proc. of AIME '91, Springer Verlag.Google Scholar
  4. 4).
    Andreassen, S., 1992a. Knowledge representation by extended linear models. In: Deep Models for Medical Knowledge Engineering (ed. E. Keravnou), Elsevier, pp 129–145.Google Scholar
  5. 5).
    Andreassen, S., 1992b. Planning of therapy and tests in causal probabilistic networks. Artificial Intelligence in Medicine, 4, 227–241.CrossRefGoogle Scholar
  6. 6).
    Andreassen, S., Benn, J.J., Hovorka, R., Olesen, K.G., and Carson, E.R., 1994. A probabilistic approach to glucose prediction and insulin dose adjustment — Description of a metabolic model and pilot evaluation study. Computer Methods and Programs in Biomedicine, 41, 153–165.PubMedGoogle Scholar
  7. 7).
    Jensen, F.V., Lauritzen, S.L., and Olesen, K.G., 1990. Bayesian updating in causal probabilistic networks by local computations. Computational Statistics Quarterly, 4, 269–282.Google Scholar
  8. 8).
    Howard, R.A.,□and Matheson, J.E., 1984. Influence diagrams. In: The principles and application of decision analysis (eds. Howard, R.A.,□and Matheson, J.E.), vol. II, Ch. 37, Srategic decision group, pp. 719–762.Google Scholar
  9. 9).
    Hovorka, R., Andreassen, S., Benn, J.J., Olesen, K.G., and Carson, E.R., 1992. Causal probabilistic network modelling. An illustration of its role in the management of chronic diseases. IBM Systems Journal, 31(4), 635–648. Reprinted in: 1993 Yearbook of Medical Informatics (eds. J.V. Bemmel and A.T. McCray), Stuttgart: Schattauer-IMIA, 1993, pp. 328–340.Google Scholar
  10. 10).
    Kjærulff, U., 1993. Aspects of efficiency improvements in Bayesian networks, Ph.D. Thesis, Aalborg University.Google Scholar
  11. 11).
    Lauritzen, S.L., and Spiegelhalter, D.J., 1988. Local computations with probabilities on graphical structures and their application to expert systems. J. Royal Statist. Soc., B50, 157–224.Google Scholar
  12. 12).
    Pearl, J., 1986. Fusion, propagation and structuring in belief networks. Artificial Intelligence, 29, 241–288.MathSciNetGoogle Scholar
  13. 13).
    Pearl, J., 1988. Probabilistic reasoning in intelligent systems; Networks of plausible inference, Morgan Kaufmann.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • O. K. Hejlesen
    • 1
  • S. Andreassen
    • 1
  • S. K. Andersen
    • 1
  1. 1.Department of Medical Informatics and Image Analysis, Institute of Electronic SystemsAalborg UniversityAalborgDenmark

Personalised recommendations