Case-Based Reasoning Applied to Medical Diagnosis and Treatment

Blanco, Xiomara; Rodríguez González, Sara; Corchado Rodríguez, Juan Manuel; Zato Domínguez, Davinia Carolina

Título

dc.contributor.author	Blanco, Xiomara
dc.contributor.author	Rodríguez González, Sara
dc.contributor.author	Corchado Rodríguez, Juan Manuel
dc.contributor.author	Zato Domínguez, Davinia Carolina
dc.date.accessioned	2017-09-06T09:14:02Z
dc.date.available	2017-09-06T09:14:02Z
dc.date.issued	2013
dc.identifier.citation	Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing. Volumen 217, pp. 137-146.
dc.identifier.isbn	978-3-319-00550-8 (Print) / 978-3-319-00551-5 (Online)
dc.identifier.issn	2194-5357 (Print) / 2194-5365 (Online)
dc.identifier.uri	http://hdl.handle.net/10366/134834
dc.description.abstract	The Case-Based Reasoning (CBR) is an appropriate methodology to apply in diagnosis and treatment. Research in CBR is growing and there are shortcomings, especially in the adaptation mechanism. In this paper, besides presenting a methodological review of the technology applied to the diagnostics and health sector published in recent years, a new proposal is presented to improve the adaptation stage. This proposal is focused on preparing the data to create association rules that help to reduce the number of cases and facilitate learning adaptation rules.
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	Case-Based Reasoning Applied to Medical Diagnosis and Treatment
dc.type	info:eu-repo/semantics/conferenceObject
dc.rights.accessRights	info:eu-repo/semantics/openAccess