Prognostic Bayesian networks II: An application in the domain of cardiac surgery
A prognostic Bayesian network (PBN) is new type of prognostic model that implements a dynamic, process-oriented view on prognosis. In a companion article, the rationale of the PBN is described, and a dedicated learning procedure is presented. This article presents an application hereof in the domain of cardiac surgery. A PBN is induced from clinical data of cardiac surgical patients using the proposed learning procedure; hospital mortality is used as outcome variable. The predictive performance of the PBN is evaluated on an independent test set, and results were compared to the performance of a network that was induced using a standard algorithm where candidate networks are selected using the minimal description length principle. The PBN is embedded in the prognostic system ProCarSur; a prototype of this system is presented. This application shows PBNs as a useful prognostic toot in medical processes. In addition, the article shows the added value of the PBN learning procedure. (C) 2007 Elsevier Inc. All rights reserved.
bayesian network cardiac surgery prognostic model health care process