Probabilistic models such as Bayesian networks [6] are well suited for medical decision support and are the basis of many successful applications [1],[3],[4],[8],[9],[10]. Bayesian networks provide a rigorous and efficient framework for inference, i.e. for calculating the probability of each
stochastic variable given a set of observations. However, knowledge acquisition and generation of the network are still demanding
tasks when large medical domains have to be modelled.