Objective Bayesian Nets for Systems Modelling and Prognosis in Breast Cancer

Abstract

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.

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Citations of this work

Interpreting causality in the health sciences.Federica Russo & Jon Williamson - 2007 - International Studies in the Philosophy of Science 21 (2):157 – 170.
Objective Bayesian nets for integrating consistent datasets.Jürgen Landes & Jon Williamson - 2022 - Journal of Artificial Intelligence Research 74:393-458.
Models in medicine.Michael Wilde & Jon Williamson - 2016 - In Miriam Solomon, Jeremy R. Simon & Harold Kincaid (eds.), The Routledge Companion to Philosophy of Medicine. Routledge.

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