ProCarSur: A System for Dynamic Prognostic Reasoning in Cardiac Surgery

  • Authors:

  • Niels Peek;Marion Verduijn;Winston G. Sjoe-Sjoe;Peter J. Rosseel;Evert Jonge;Bas A. Mol

  • Affiliations:

  • Dept. of Medical Informatics, Academic Medical Center, Amsterdam,;Dept. of Medical Informatics, Academic Medical Center, Amsterdam, and Dept. of Biomedical Engineering, University of Technology, Eindhoven,;Dept. of Medical Informatics, Academic Medical Center, Amsterdam,;Dept. of Anesthesia and Intensive Care, Amphia Hospital, Breda,;Dept. of Intensive Care Medicine, Academic Medical Center, Amsterdam,;Dept. of Biomedical Engineering, University of Technology, Eindhoven, and Dept. of Cardio-thoracic Surgery, Academic Medical Center, Amsterdam,

  • Venue:
  • AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
  • Year:
  • 2007

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Abstract

We present the ProCarSur system for prognostic reasoning in the domain of cardiac surgery. The system has a three-tiered architecture consisting of a Bayesian network, a task layer, and a graphical user interface. In contrast to traditional prognostic tools, that are usually based on logistic regression, ProCarSur implements a dynamic, process-oriented view on prognosis. The system distinguishes between the various phases of peri-surgical care, explicates the scenarios that lead to different clinical outcomes, and can be used to update predictions when new information becomes available. To support users in their interaction with the Bayesian network, a set of predefined prognostic reasoning tasks is implemented in the task layer. The user communicates with the system through an interface that hides the underlying Bayesian network and aggregates the results of probabilistic inferences.