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Please use this identifier to cite or link to this item: https://dspace.ucuenca.edu.ec/handle/123456789/42405
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dc.contributor.authorRobles Bykbaev, Vladimir
dc.contributor.authorLoja Morocho, Andres Fernando
dc.contributor.authorRocano Portoviejo, Jessica Noemi
dc.contributor.authorVega Crespo, Bernardo Jose
dc.contributor.authorVerhoeven, Veronique
dc.date.accessioned2023-07-17T16:06:26Z-
dc.date.available2023-07-17T16:06:26Z-
dc.date.issued2023
dc.identifier.isbn000-000-000-0
dc.identifier.issn2367-3370, e 2367-3389
dc.identifier.urihttp://dspace.ucuenca.edu.ec/handle/123456789/42405-
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-031-33258-6_23
dc.descriptionAccording to the World Health Organization (WHO), cervical cancer (CC) is an illness that has taken more than 342,000 female lives in 2020 and is considered the fourth cause of death in the world. In the rural areas of countries like Ecuador, there is no existence of low-cost tools for women who need to perform a self-screening exam and doctors who need to report cases based on artificial vision. For these reasons, in this article, we present the results of the first stage of development of the ecosystems aimed at the early detection of CC in rural areas. This ecosystem is based on a mobile application used to take photos during self-screening, a web tool to store and manage the image and diagnosis, and a module to classify images using deep learning
dc.description.abstractAccording to the World Health Organization (WHO), cervical cancer (CC) is an illness that has taken more than 342,000 female lives in 2020 and is considered the fourth cause of death in the world. In the rural areas of countries like Ecuador, there is no existence of low-cost tools for women who need to perform a self-screening exam and doctors who need to report cases based on artificial vision. For these reasons, in this article, we present the results of the first stage of development of the ecosystems aimed at the early detection of CC in rural areas. This ecosystem is based on a mobile application used to take photos during self-screening, a web tool to store and manage the image and diagnosis, and a module to classify images using deep learning
dc.language.isoes_ES
dc.publisherSpringer
dc.sourceInternational Conference on Information Technology & Systems
dc.subjectDeep learning
dc.subjectMobile applications
dc.subjectRural areas
dc.subjectCervical Cancer
dc.subjectComputer visio
dc.titleIntelligent System to Provide Support in the Analysis of Colposcopy Images Based on Artificial Vision and Deep Learning: A First Approach for Rural Environments in Ecuador
dc.title.alternative
dc.typeARTÍCULO DE CONFERENCIA
dc.description.cityCusco
dc.ucuenca.idautor0000-0002-7645-8793
dc.ucuenca.idautor0107137416
dc.ucuenca.idautor0104968946
dc.ucuenca.idautor0102146917
dc.ucuenca.idautor0000-0002-3708-6501
dc.identifier.doi10.1007/978-3-031-33258-6_23
dc.ucuenca.embargoend2050-12-31
dc.ucuenca.versionVersión publicada
dc.ucuenca.embargointerno2050-12-31
dc.ucuenca.areaconocimientounescoamplio09 - Salud y Bienestar
dc.ucuenca.afiliacionVerhoeven, V., Universidad de Amberes (University of Antwerp), Amberes, Belgica
dc.ucuenca.afiliacionLoja, A., Universidad Politécnica Salesiana (UPS), Cuenca, Ecuador
dc.ucuenca.afiliacionRocano, J., Universidad Politécnica Salesiana (UPS), Cuenca, Ecuador
dc.ucuenca.afiliacionVega, B., Universidad de Cuenca, Facultad de Ciencias Médicas, Cuenca, Ecuador
dc.ucuenca.afiliacionRobles, V., Universidad Politécnica Salesiana (UPS), Cuenca, Ecuador
dc.ucuenca.correspondenciaRobles Bykbaev, Vladimir, vrobles@ups.edu.ec
dc.ucuenca.volumenVolumen 1
dc.ucuenca.indicebibliograficoSCOPUS
dc.ucuenca.factorimpacto0.151
dc.ucuenca.cuartilQ4
dc.ucuenca.numerocitaciones0
dc.ucuenca.areaconocimientofrascatiamplio3. Ciencias Médicas y de la Salud
dc.ucuenca.paisPERU
dc.ucuenca.conferenciaInformation Technology and Systems
dc.ucuenca.areaconocimientofrascatiespecifico3.3 Ciencias de la Salud
dc.ucuenca.areaconocimientofrascatidetallado3.3.9 Enfermedades Infecciosas
dc.ucuenca.areaconocimientounescoespecifico091 - Salud
dc.ucuenca.areaconocimientounescodetallado0912 - Medicina
dc.ucuenca.fechainicioconferencia2023-02-08
dc.ucuenca.fechafinconferencia2023-02-10
dc.ucuenca.organizadorconferenciaICITS 2023
dc.ucuenca.comiteorganizadorconferenciaICITS 2023
dc.ucuenca.urifuentehttps://link.springer.com/conference/icitss
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