Piskorski J., Stanisławska K., Dziarmaga M., Minczykowski A., Wykretowicz A, Wysocki H.
data mining, medical visualization, PTCA, computationally intensive statistical analysis
We present an exploratory study of a group of patients (150) who have undergone precutaneous transluminal coronary angioplasty with the use of drug eluting stents. We concentrate on the most often studied rare adverse event, i.e. death, as well as the still unexplored cancer variable. The aim of the study is to identify possible statistical hypotheses for a subsequent, large sample study. The results of this study may lead to a change in the therapy administered after precutaneous coronary interventions which will reduce the mortality rate. To achieve this, we use clustering techniques such as hierarchical cluster analysis, principal components methods and interactive brushing. We show that death cases cluster in the space defined by the available variables, while the cancer cases do not seem to cluster.