\LHead{Background}\\

The availability of huge data sets may lead to important changes in health care by mining those data for the development of decision support sytems. Probabilistic grapical models are considered appropriate tools for data mining. Soon, the digitization of the Dutch breast cancer screening will start giving a unique opportunity to mine these data for the development of decision support systems in Radiology. \\

\LHead{Aims} \\

The further development of CAD technology using Bayesian Networks to address the problem of interpretation failures by radiologists.
\begin{itemize}
\item Develop novel classification methods such that:
 \begin{itemize}
   \item Medical knowledge can be incorporated
   \item Classifiers are faithful w.r.t. the data
 \end{itemize}
\item Develop new image representation techniques
\item Extend mammographic breast cancer data sets
\item Determine experimentally how to use CAD as a decision aid in a practical context
\end{itemize}
