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Applying evidence-based medicine in telehealth: an interactive pattern recognition approximation

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Applying evidence-based medicine in telehealth: an interactive pattern recognition approximation

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dc.contributor.author Fernández Llatas, Carlos es_ES
dc.contributor.author Meneu, Teresa es_ES
dc.contributor.author Traver Salcedo, Vicente es_ES
dc.contributor.author Benedí Ruiz, José Miguel es_ES
dc.date.accessioned 2014-07-02T09:23:47Z
dc.date.available 2014-07-02T09:23:47Z
dc.date.issued 2013-10-31
dc.identifier.issn 1660-4601
dc.identifier.uri http://hdl.handle.net/10251/38515
dc.description.abstract [EN] Born in the early nineteen nineties, evidence-based medicine (EBM) is a paradigm intended to promote the integration of biomedical evidence into the physicians daily practice.This paradigm requires the continuous study of diseases to provide the best scientific knowledge for supporting physicians in their diagnosis and treatments in a close way. Within this paradigm, usually, health experts create and publish clinical guidelines, which provide holistic guidance for the care for a certain disease. The creation of these clinical guidelines requires hard iterative processes in which each iteration supposes scientificc progress in the knowledge of the disease. To perform this guidance through telehealth, the use of formal clinical guidelines will allow the building of care processes that can be interpreted and executed directly by computers. In addition, the formalization of clinical guidelines allows for the possibility to build automatic methods, using pattern recognition techniques, to estimate the proper models, as well as the mathematical models for optimizing the iterative cycle for the continuous improvement of the guidelines. However, to ensure the efficiency of the system, it is necessary to build a probabilistic model of the problem. In this paper, an interactive pattern recognition approach to support professionals in evidence-based medicine is formalized. es_ES
dc.description.sponsorship The authors want to acknowledge the European Commision for their suport via MOSAIC (ICT-FP7-600914) and HEARTWAYS (ICT-SME-315659) EU-Projects en_EN
dc.format.extent 12 es_ES
dc.language Inglés es_ES
dc.publisher MDPI es_ES
dc.relation.ispartof International Journal of Environmental Research and Public Health es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Evidence based medicine es_ES
dc.subject Interactive pattern recognition es_ES
dc.subject Personalized medicine es_ES
dc.subject Clinical guidelines es_ES
dc.subject Probabilistic model es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Applying evidence-based medicine in telehealth: an interactive pattern recognition approximation es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/ijerph10115671
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/600914 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/315659/EU
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario Mixto Tecnológico de Informática - Institut Universitari Mixt Tecnològic d'Informàtica es_ES
dc.description.bibliographicCitation Fernández Llatas, C.; Meneu, T.; Traver Salcedo, V.; Benedí Ruiz, JM. (2013). Applying evidence-based medicine in telehealth: an interactive pattern recognition approximation. International Journal of Environmental Research and Public Health. 10(11):5671-5682. https://doi.org/10.3390/ijerph10115671 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://www.mdpi.com/1660-4601/10/11/5671 es_ES
dc.description.upvformatpinicio 5671 es_ES
dc.description.upvformatpfin 5682 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 10 es_ES
dc.description.issue 11 es_ES
dc.relation.senia 251741
dc.identifier.pmid 24185841 en_EN
dc.identifier.pmcid PMC3863864 en_EN
dc.contributor.funder European Commission


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