M-Health System for detecting Covid-19 in Chest X-Rays using deep learning and data security approaches
Fecha
2022
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Universidad Católica de Cuenca
Resumen
Descripción
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
Palabras clave
Deep Learning,, X-RAY,, Security,, Software,, COVID-19
