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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)

Abstract

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.

Keywords

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.

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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

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