Objective Bayesian nets for systems modelling and prognosis in breast cancer

Nagl, Sylvia and Williams, Matthew and Williamson, Jon (2008) Objective Bayesian nets for systems modelling and prognosis in breast cancer. In: Holmes, Dawn and Jain, Lakhmi C., eds. Innovations in Bayesian Networks: Theory and Applications. Studies in Computational Intelligence, 156 . Springer, Berlin, pp. 131-168. ISBN 9783540850656. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Cancer treatment decisions should be based on all available evidence. But this evidence is complex and varied: it includes not only the patient's symptoms and expert knowledge of the relevant causal processes, but also clinical databases relating to past patients, databases of observations made at the molecular level, and evidence encapsulated in scientific papers and medical informatics systems. Objective Bayesian nets offer a principled path to knowledge integration, and we show in this chapter how they can be applied to integrate various kinds of evidence in the cancer domain. This is important from the systems biology perspective, which needs to integrate data that concern different levels of analysis, and is also important from the point of view of medical informatics.

Item Type: Book section
Subjects: B Philosophy. Psychology. Religion > B Philosophy (General)
Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Faculties > Humanities > School of European Culture and Languages
Depositing User: Jon Williamson
Date Deposited: 21 Jul 2009 10:20
Last Modified: 02 Jun 2014 08:32
Resource URI: https://kar.kent.ac.uk/id/eprint/20880 (The current URI for this page, for reference purposes)
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