eneric causal probabilistic networks : A solution o a problem of transferability in edical decision support

Causal probabilistic networks provide a natural framework for representation of medical knowledge, allowing clinical experts to encode assumptions about causal dependencies between stochastic variables. Application inmedical decision support has produced promising results. However, model features and parameters may vary geoor demographically. Therefore methods are needed that allow for easy adjustment of the model to a change in conditions.We present amethod to represent causal probabilistic networks generically that