The second edition of this bestseller provides a practical and accessible introduction to the
main concepts, foundation, and applications of Bayesian networks. This edition contains a …

We argue that the health sciences make causal claims on the basis of evidence both of
physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of …

Purpose Despite significant progress in the molecular understanding of medulloblastoma,
stratification of risk in patients remains a challenge. Focus has shifted from clinical …

This paper addresses a data integration problem: given several mutually consistent datasets
each of which measures a subset of the variables of interest, how can one construct a …

This chapter presents an overview of the major interpretations of probability followed by an
outline of the objective Bayesian interpretation and a discussion of the key challenges it …

In this chapter I discuss connections between machine learning and the philosophy of
science. First I consider the relationship between the two disciplines. There is a clear …

Model integration–the process by which different modelling efforts can be brought together
to simulate the target system–is a core technology in the field of Systems Biology. In the work …

The study of multidimensional well-being has long recognized the importance of formalizing
the interaction between dimensions, but came short of treating this formally. In this paper, we …

Human civilization as we know it would look very different were it not for collective efforts to
maintain and improve population health. Access to the means that support individual and …

In the multidimensional well-being literature, it has been long advocated that it is important
to consider how the different well-being domains interact. Nevertheless, none of the existing …