Contrast set mining for distinguishing between similar diseases

Petra Kralj*, Nada Lavrač, Dragan Gamberger, Antonija Krstačić

*Corresponding author for this work

Research output: Contribution to Book/Report typesConference contributionpeer-review

Abstract (may include machine translation)

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.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine - 11th Conference on Artificial Intelligence in Medicine, AIME 2007, Proceedings
PublisherSpringer Verlag
Pages109-118
Number of pages10
ISBN (Print)3540735984, 9783540735984
DOIs
StatePublished - 2007
Externally publishedYes
Event11th Conference on Artificial Intelligence in Medicine, AIME 2007 - Amsterdam, Netherlands
Duration: 7 Jul 200711 Jul 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4594 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th Conference on Artificial Intelligence in Medicine, AIME 2007
Country/TerritoryNetherlands
CityAmsterdam
Period7/07/0711/07/07

Fingerprint

Dive into the research topics of 'Contrast set mining for distinguishing between similar diseases'. Together they form a unique fingerprint.

Cite this