Using CBR Systems for Leukemia Classification

Corchado Rodríguez, Juan Manuel; De Paz, Juan F.

Título

dc.contributor.author	Corchado Rodríguez, Juan Manuel
dc.contributor.author	De Paz, Juan F.
dc.date.accessioned	2017-09-06T09:15:42Z
dc.date.available	2017-09-06T09:15:42Z
dc.date.issued	2008
dc.identifier.citation	Hybrid Artificial Intelligence Systems Lecture Notes in Computer Science. Lecture Notes in Computer Science. Volumen 5271, pp. 688-695.
dc.identifier.isbn	978-3-540-87655-7 (Print) / 978-3-540-87656-4 (Online)
dc.identifier.issn	0302-9743 (Print) / 1611-3349 (Online)
dc.identifier.uri	http://hdl.handle.net/10366/135011
dc.description.abstract	The continuous advances in genomics, and specifically in the field of transcriptome, require novel computational solutions capable of dealing with great amounts of data. Each expression analysis needs different techniques to explore the data and extract knowledge which allow patients classification. This paper presents a hybrid systems based on Case-based reasoning (CBR) for automatic classification of leukemia patients from Exon array data. The system incorporates novel algorithms for data mining that allow to filter and classify. The system has been tested and the results obtained are presented in this paper.
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.publisher	Springer Science + Business Media
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject	Computer Science
dc.title	Using CBR Systems for Leukemia Classification
dc.type	info:eu-repo/semantics/conferenceObject
dc.rights.accessRights	info:eu-repo/semantics/openAccess