Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques

Domínguez Muñoz, Manuel; Aroba Páez, Javier; González Enríquez, José; Ramos Román, Isabel; Lucena Soto, José Manuel; Escalona Cuaresma, María José

doi:10.5220/0004969503250330

Ponencia

dc.creator	Domínguez Muñoz, Manuel	es
dc.creator	Aroba Páez, Javier	es
dc.creator	González Enríquez, José	es
dc.creator	Ramos Román, Isabel	es
dc.creator	Lucena Soto, José Manuel	es
dc.creator	Escalona Cuaresma, María José	es
dc.date.accessioned	2017-05-02T11:40:19Z
dc.date.available	2017-05-02T11:40:19Z
dc.date.issued	2014
dc.identifier.citation	Domínguez Muñoz, M., Aroba, J., González Enríquez, J., Ramos Román, I., Lucena Soto, J.M. y Escalona Cuaresma, M.J. (2014). Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques. En ICEIS 2014: 16th International Conference on Enterprise Information Systems (325-330), Lisboa, Portugal: ScitePress Digital Library.
dc.identifier.isbn	978-989-758-027-7	es
dc.identifier.uri	http://hdl.handle.net/11441/59099
dc.description.abstract	Virological events in HIV-infected patients can rise with no apparent reason. Therefore, when they appear, immunologists or medical doctors do not know whether they will produce other future virological events or they will entail relevant clinical consequences. This paper presents the results of applying Prefurge to HIV- infected patients’ clinical data, with the aim of obtaining rules and information about this set of clinical trials data that will relate these kinds of virological events.	es
dc.description.sponsorship	Junta de Andalucía TIC-5789	es
dc.format	application/pdf	es
dc.language.iso	eng	es
dc.publisher	ScitePress Digital Library	es
dc.relation.ispartof	ICEIS 2014: 16th International Conference on Enterprise Information Systems (2014), p 325-330
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	HIV	es
dc.subject	Virological Events	es
dc.subject	Prefurge	es
dc.subject	Unsupervised Learning	es
dc.title	Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques	es
dc.type	info:eu-repo/semantics/conferenceObject	es
dcterms.identifier	https://ror.org/03yxnpp24
dc.type.version	info:eu-repo/semantics/publishedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos	es
dc.relation.projectID	TIC-5789	es
dc.relation.publisherversion	http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220%2f0004969503250330	es
dc.identifier.doi	10.5220/0004969503250330	es
dc.contributor.group	Universidad de Sevilla. TIC021: Ingeniería Web y Testing Temprano (IWT2)	es
idus.format.extent	6	es
dc.publication.initialPage	325	es
dc.publication.endPage	330	es
dc.eventtitle	ICEIS 2014: 16th International Conference on Enterprise Information Systems	es
dc.eventinstitution	Lisboa, Portugal	es
dc.relation.publicationplace	Lisboa	es
dc.contributor.funder	Junta de Andalucía

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