A Belief Network Model for Interpretation of ICU Data

Reference: Rutledge, G. W.; Andersen, S. K.; Polaschek, J. X.; & Fagan, L. M. A Belief Network Model for Interpretation of ICU Data. 1990.

Abstract: Belief networks provide a causal probabilistic framework for the representation of medical knowledge. We have developed VPnet, a belief-network model of the pathophysiology of patients in the intensive-care unit (ICU), and have incorporated this belief-network in a system _VentPlan_ that assists in the care and monitoring of patients in the ICU. VPnet converts patient observations into probability distributions for a set of physiological parameters used by VentPlan's mathematical model. VPnet represents the uncertainty of data observations explicitly and implements a model of increasing uncertainty as the time from an observation increases. We have evaluated VPnet using sets of inputs corresponding to a variety of clinical states, and we show calculated physiologic parameter distributions appropriate for the clinical state. Evaluation of complex belief-network models is difficult due to the lack of a gold standard for comparison, and because there is a large number of possible sets of input states.

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