Logo Repositorio Institucional

Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/42405
Title: Intelligent 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
Other Titles: 
Authors: Robles Bykbaev, Vladimir
Loja Morocho, Andres Fernando
Rocano Portoviejo, Jessica Noemi
Vega Crespo, Bernardo Jose
Verhoeven, Veronique
metadata.dc.ucuenca.correspondencia: Robles Bykbaev, Vladimir, vrobles@ups.edu.ec
Keywords: Deep learning
Mobile applications
Rural areas
Cervical Cancer
Computer visio
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 3. Ciencias Médicas y de la Salud
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 3.3.9 Enfermedades Infecciosas
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 3.3 Ciencias de la Salud
metadata.dc.ucuenca.areaconocimientounescoamplio: 09 - Salud y Bienestar
metadata.dc.ucuenca.areaconocimientounescodetallado: 0912 - Medicina
metadata.dc.ucuenca.areaconocimientounescoespecifico: 091 - Salud
Issue Date: 2023
metadata.dc.ucuenca.embargoend: 31-Dec-2050
metadata.dc.ucuenca.volumen: Volumen 1
metadata.dc.source: International Conference on Information Technology & Systems
metadata.dc.identifier.doi: 10.1007/978-3-031-33258-6_23
Publisher: Springer
metadata.dc.description.city: 
Cusco
metadata.dc.type: ARTÍCULO DE CONFERENCIA
Abstract: 
According 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
Description: 
According 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
URI: http://dspace.ucuenca.edu.ec/handle/123456789/42405
https://link.springer.com/chapter/10.1007/978-3-031-33258-6_23
metadata.dc.ucuenca.urifuente: https://link.springer.com/conference/icitss
ISBN: 000-000-000-0
ISSN: 2367-3370, e 2367-3389
Appears in Collections:Artículos

Files in This Item:
File SizeFormat 
documento.pdf
  Until 2050-12-31
346.06 kBAdobe PDFView/Open Request a copy


This item is protected by original copyright



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Centro de Documentacion Regional "Juan Bautista Vázquez"

Biblioteca Campus Central Biblioteca Campus Salud Biblioteca Campus Yanuncay
Av. 12 de Abril y Calle Agustín Cueva, Telf: 4051000 Ext. 1311, 1312, 1313, 1314. Horario de atención: Lunes-Viernes: 07H00-21H00. Sábados: 08H00-12H00 Av. El Paraíso 3-52, detrás del Hospital Regional "Vicente Corral Moscoso", Telf: 4051000 Ext. 3144. Horario de atención: Lunes-Viernes: 07H00-19H00 Av. 12 de Octubre y Diego de Tapia, antiguo Colegio Orientalista, Telf: 4051000 Ext. 3535 2810706 Ext. 116. Horario de atención: Lunes-Viernes: 07H30-19H00