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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/article | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess |
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