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.
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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.
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© 2001 Springer-Verlag Berlin Heidelberg
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de Bruijn, N., Lucas, P., Schurink, K., Bonten, M., Hoepelman, A. (2001). Using Temporal Probabilistic Knowledge for Medical Decision Making. In: Quaglini, S., Barahona, P., Andreassen, S. (eds) Artificial Intelligence in Medicine. AIME 2001. Lecture Notes in Computer Science(), vol 2101. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48229-6_33
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DOI: https://doi.org/10.1007/3-540-48229-6_33
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