| 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 | |