Evidence Synthesis Using Bayesian Belief Networks

  • Zhifang Ni
  • Lawrence D. Phillips
  • George B. Hanna


Bayesian belief networks (BBNs) are graphical tools for reasoning with uncertainties. In BBNs, uncertain events are represented as nodes and their relationships as links, with missing links indicating conditional independence. BBNs perform belief updating when new information becomes available; they can handle incomplete information and capture expert judgments along with data. BBNs provide a normative framework for synthesizing uncertain evidence.


Bayesian Network Conditional Independence Expert Judgment Bayesian Belief Network Uncertain Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Bayesian belief network


Negative predictive value


Positive predictive value



The authors wish to thank Norman Fenton and William Marsh for insightful discussions on Bayesian networks.


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Copyright information

© Springer London 2011

Authors and Affiliations

  • Zhifang Ni
    • 1
  • Lawrence D. Phillips
  • George B. Hanna
  1. 1.Department of Surgery and CancerImperial College LondonLondonUK

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