Contrast Set Mining for Distinguishing Between Similar Diseases

The task addressed and the method proposed in this paper aim at improved understanding of differences between similar diseases. In particular we address the problem of distinguishing between thrombolic brain stroke and embolic brain stroke as an application of our approach of contrast set mining through subgroup discovery. We describe methodological lessons learned in the analysis of brain ischaemia data and a practical implementation of the approach within an open source data mining toolbox.

• Type: Conference
• Year: 2007
• Where: AIME
• Authors: Petra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic
• Keywords: AIME 2007, Artificial Intelligence, Brain Ischaemia Data, Brain Stroke, Thrombolic Brain Stroke