Knowledge Acquisition and Automated Generation of Bayesian Networks for a Medical Dialogue and Advisory System

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.