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Bayesian networks for cardiovascular monitoring
Jennifer M Roberts1, Tushar A Parlikar, Thomas Heldt
1Dept. of Electrical Engineering & Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Abstract:
Bayesian Networks provide a flexible way of incorporating different types of information into a single probabilistic model. In a medical setting, one can use these networks to create a patient model that incorporates lab test results, clinician observations, vital signs, and other forms of patient data. In this paper, we explore a simple Bayesian Network model of the cardiovascular system and evaluate its ability to predict unobservable variables using both real and simulated patient data.
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