Combining argumentation and bayesian nets for breast cancer prognosis

Authors
Jon Williamson
University of Kent
Abstract
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

Causality: Models, Reasoning, and Inference.Judea Pearl - 2000 - Cambridge University Press.
Causation, Prediction, and Search.Peter Spirtes, Clark Glymour & Richard Scheines - 1996 - British Journal for the Philosophy of Science 47 (1):113-123.
Argument-Based Extended Logic Programming with Defeasible Priorities.Henry Prakken & Giovanni Sartor - 1997 - Journal of Applied Non-Classical Logics 7 (1-2):25-75.

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

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