Discovering Emerging Patterns from Medical Opinions about the Decrease of Autopsies Performed in a Mexican Hospital

Abstract

Emerging Pattern Mining (EPM) is a data mining task that finds discriminative characteristics between classes or data sets. In this paper, several EPM algorithms were applied to a data set which contains the opinions of the medical staff from a Mexican hospital about the decrease of autopsies. We consider two attributes as class labels: motives for autopsy acceptance and motives for autopsy rejection in order to find aspects like medical training and medical experience that imply that physicians consider reasons for requesting or rejecting autopsies.