M-Health System for detecting Covid-19 in Chest X-Rays using deep learning and data security approaches

Delgado Plaza, Johnny Leonardo

M-Health System for detecting Covid-19 in Chest X-Rays using deep learning and data security approaches

dc.contributor.advisor	Quevedo Sacoto, Andrés Sebastián
dc.contributor.author	Delgado Plaza, Johnny Leonardo
dc.coverage	Cuenca-Ecuador	es_ES
dc.date.accessioned	2022-12-16T16:27:45Z
dc.date.available	2022-12-16T16:27:45Z
dc.date.issued	2022
dc.description	Advances in predicting different types of pathologies in medical images have been significant in the last decade, thanks to the performance and efficiency of models trained with deep learning approaches. In this context, the prediction of the COVID-19 disease in chest X-Rays has been no exception. However, the proposed models are not always put into production and those that do not consider data security a system requirement. In this work, we propose creating a mobile application for detecting COVID-19 disease in chest X-rays using Deep Learning and data security approaches. Our prediction model has a sensitivity of 92% and a specificity of 90%. Our application implements the OAuth 2.0 access delegation standard for system access authorization	es_ES
dc.description.uri	Trabajo de investigación	es_ES
dc.format	application/pdf	es_ES
dc.identifier.other	19B-2022-TC1
dc.identifier.uri	https://dspace.ucacue.edu.ec/handle/ucacue/13151
dc.language.iso	eng	es_ES
dc.publisher	Universidad Católica de Cuenca	es_ES
dc.rights	info:eu-repo/semantics/embargoedAccess	es_ES
dc.source	UNIVERSIDAD CATÓLICA DE CUENCA	es_ES
dc.subject	Deep Learning,	es_ES
dc.subject	X-RAY,	es_ES
dc.subject	Security,	es_ES
dc.subject	Software,	es_ES
dc.subject	COVID-19	es_ES
dc.title	M-Health System for detecting Covid-19 in Chest X-Rays using deep learning and data security approaches	es_ES
dc.type	info:eu-repo/semantics/article	es_ES
thesis.degree.level	Maestría	es_ES