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Clinical evidence framework for Bayesian networks
Authors:Barbaros Yet  Zane B Perkins  Nigel R M Tai  D William R Marsh
Affiliation:1.School of Electronic Engineering and Computer Science,Queen Mary University of London,London,UK;2.Centre for Trauma Science,Queen Mary University of London,London,UK;3.The Royal London Hospital,London,UK;4.Department of Industrial Engineering,Hacettepe University,Ankara,Turkey
Abstract:There is poor uptake of prognostic decision support models by clinicians regardless of their accuracy. There is evidence that this results from doubts about the basis of the model as the evidence behind clinical models is often not clear to anyone other than their developers. In this paper, we propose a framework for representing the evidence-base of a Bayesian network (BN) decision support model. The aim of this evidence framework is to be able to present all the clinical evidence alongside the BN itself. The evidence framework is capable of presenting supporting and conflicting evidence, and evidence associated with relevant but excluded factors. It also allows the completeness of the evidence to be queried. We illustrate this framework using a BN that has been previously developed to predict acute traumatic coagulopathy, a potentially fatal disorder of blood clotting, at early stages of trauma care.
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