Bayesian network

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Bayesian network

A form of artificial intelligence—named for Bayes’ theorem—which calculates probability based on a group of related or influential signs. Once a Bayesian network AI is taught the symptoms and probable indicators of a particular disease, it can assess the probability of that disease based on the frequency or number of signs in a patient.
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Bayesian Networks. Bayesian network (BN) is a directed acyclic graph represented with pairs N = {(V, E), P}.
Modification of the Influence Model: Bayesian Network. First, this study adopted a focused group discussion adaptation of the model proposed by Liao et al.
The Analysis of the obtained results by the methodology of converting the fault tree into bayesian networks allowed to identify the undesirable and critical components, and contributed in using the targeted preventive maintenance in order to increase the system's reliability and availability.
ALGORITHM 1: Pseudo-code for generating Bayesian Networks from Modelica-based models.
According to the three kinds of characteristics of abnormal events in wireless sensor networks and the experience that Bayesian network can effectively represent the probability relationship among attributes, we construct the attribute dependency model.
In this paper, we work with a dynamic Bayesian network and use spline regression to detect the nonlinear interactions between genes.
Alterovitz, "SNP-based Bayesian networks can predict oral mucositis risk in autologous stem cell transplant recipients," Oral Diseases, vol.
Bayesian networks are mathematical formalisms that allow to deal with the uncertainty that underlies the amount of human activities, measured in terms of probability.
Visualizing Inference in Bayesian Networks. Master's thesis, Delft University of Technology, 2006.

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