A Belief Network Model for Interpretation of ICU Data

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Citation: Geoffrey W. Rutledge and Stig K. Andersen and Jeanette X. Polaschek and Lawrence M. Fagan. (1990) A Belief Network Model for Interpretation of ICU Data. In , 1990.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Geoffrey W. Rutledge and Stig K. Andersen and Jeanette X. Polaschek and Lawrence M. Fagan
title A Belief Network Model for Interpretation of ICU Data
number KSL-90-49
institution Knowledge Systems, AI Laboratory
year 1990
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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.

KSL Technical Report ID: KSL-90-49
Facts about A Belief Network Model for Interpretation of ICU DataRDF feed
Abstract Belief networks provide a causal probabili … 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. e number of possible sets of input states.
Author Geoffrey W. Rutledge and Stig K. Andersen and Jeanette X. Polaschek and Lawrence M. Fagan  +
Bibtype techreport  +
Has author Geoffrey W. Rutledge and Stig K. Andersen and Jeanette X. Polaschek and Lawrence M. Fagan  +
Has identifier KSL-90-49  +
Has publishing details 1990  +
Has title A Belief Network Model for Interpretation of ICU Data  +
Has year 1990  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-90-49  +
Number KSL-90-49  +
Process note YES  +
Title A Belief Network Model for Interpretation of ICU Data  +
Year 1990  +
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