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Using Temporal Probabilistic Knowledge for Medical Decision Making

  • Nicolette de Bruijn
  • Peter Lucas
  • Karin Schurink
  • Marc Bonten
  • Andy Hoepelman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2101)

Abstract

Time plays an important role in medical decision making, as a patient’s disease is a dynamic process that changes over time; medical doctors, therefore, have to deal with the temporal nature of these processes as well. However, it is not clear whether time is equally important in every aspect of medical decision making. This paper explores the role of time in the diagnosis and treatment of ventilator-associated pneumo- nia (VAP) in ICU patients. The aim of this study was to obtain insight into the advantages and limitations of dealing with time explicitly in the context of VAP.

Keywords

Bayesian Network Temporal Information Treatment Selection Colonisation Process Temporal Nature 
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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References

  1. 1.
    P.J.F. Lucas, N.C. de Bruijn, K. Schurink, I.M. Hoepelman. A Probabilistic and decision-theoretic approach to the management of infectious disease at the ICU. Artificial Intelligence in Medicine 19(3) (2000) 251–279.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Nicolette de Bruijn
    • 1
  • Peter Lucas
    • 2
  • Karin Schurink
    • 1
  • Marc Bonten
    • 1
  • Andy Hoepelman
    • 1
  1. 1.Department of Internal MedicineUniversity Medical Centre UtrechtUtrechtThe Netherlands
  2. 2.Department of Computing ScienceUniversity of AberdeenAberdeenUK

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