Diagnosis supporting rules of the Hepar system.

The "Hepar" system comprises a clinical database and the shell of procedures that aim at data analysis and the support of diagnosis. The database consists of hepatological patient cases. Each case is described by about 200 medical findings and histopathologically verified diagnosis. The diagnosis supporting rules of "Hepar" are based on visualizing data transformations and on the similarity based techniques. The applied linear visualizing transformations of data sets on the plane aim at separating of the groups of patients associated with different diseases. The resulting diagnostic maps by the visual inspection allow to find such cases in the database that are similar to the previously diagnosed patients. This paper examines combining of data transformations with the nearest neighbors techniques in the support of diagnosis. We report the results on the experimental comparisons of different decision rules including the feature selection procedure.