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Covid-19’s Rapid diagnosis Open platform based on X-Ray Imaging and Deep Learning
The Coronavirus epidemic first appeared in Wuhan-China on December, 31(st), 2019. This has put the world’s hospitals, clinics, testing laboratories and health administrations under pressure. As of April, 04(th), 2020, the World Health Organization reported more than 167515 confirmed cases in more th...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954644/ https://www.ncbi.nlm.nih.gov/pubmed/33747260 http://dx.doi.org/10.1016/j.procs.2020.10.088 |
Sumario: | The Coronavirus epidemic first appeared in Wuhan-China on December, 31(st), 2019. This has put the world’s hospitals, clinics, testing laboratories and health administrations under pressure. As of April, 04(th), 2020, the World Health Organization reported more than 167515 confirmed cases in more than 100 countries worldwide. The diagnosis of the epidemic will increase the burden on overburdened testing laboratories. Several screening methods have been proposed in parallel in order to facilitate and, above all, to make rapid diagnosis easier. At this level, X-Ray images seem to be a good accompanying solution for emerging countries to help rapid screening. The solution proposed in this paper consists on a collaborative and smart platform based on the Convolutional Neural Network for Classification and Detection namely VGG16. The platform ensures the fast download of the X-Ray image, with the entry of the patient’s personal information followed by the launch of a 5 seconds test. The platform generates, as a result, a PDF file containing all patient information. |
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