Combining argumentation and bayesian nets for breast cancer prognosis

We present a new framework for combining logic with probability, and demonstrate the application of this framework to breast cancer prognosis. Background knowledge concerning breast cancer prognosis is represented using logical arguments. This background knowledge and a database are used to build a Bayesian net that captures the probabilistic relationships amongst the variables. Causal hypotheses gleaned from the Bayesian net in turn generate new arguments. The Bayesian net can be queried to help decide when one argument attacks another. The Bayesian net is used to perform the prognosis, while the argumentation framework is used to provide a qualitative explanation of the prognosis.
Keywords argumentation  logic  bayes theorem  bayesian networks
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DOI 10.1007/s10849-005-9010-x
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References found in this work BETA
Peter Spirtes, Clark Glymour & Richard Scheines (1996). Causation, Prediction, and Search. British Journal for the Philosophy of Science 47 (1):113-123.

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Citations of this work BETA
Federica Russo & Jon Williamson (2007). Interpreting Causality in the Health Sciences. International Studies in the Philosophy of Science 21 (2):157 – 170.

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