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Sistema de información en la web para detección de COVID-19 en radiografías de tórax.
(Universidad Católica de Cuenca., 2022) Clavijo Santacruz, Luis David; Soria Peña, Carlos Eduardo; Quevedo Sacoto, Andrés Sebastián; 0105630388; 0105885537
In the last decade, the increase of the technology has been advanced in a gigantic steps, much of these technologies have been taken in to the medicine world, helping and keeping dangerous diseases like COVID under control. That's why that with the help of the artificial intelligence, we can predict dignostics based in torax x-rays. This research is based on the implementation of a web information system, which connects to an AI prediction server, which analyzes the presence or absence of COVID by sending digitized radiographs. This system is elavorated under the agile SCRUM framework and is designed in a friendly way so that any user can use it without major complications, also implements security provided by springboot to guarantee confydentiality, integrity and availability in data. The results of the research were satisfactory with a proyection of 85% percent as a total approval of the functionality and the content displayed, while the rest 15% of the users who tested the system had problems, nevertheless, we received the feedback necessary to improve the interface experience.