The work presents a model construction process which is a combination of the inductive learning based detection of interesting
sub- groups, comparative statistical analyses of risk factors for these groups, and expert knowledge interpretation of the
results. The induced models describe population subgroups with unproportionately high rate of the disease what might be helpful
in the prevention process.