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The coronavirus outbreak became a major concern for society worldwide.Technological innovation and ingenuity are essential to fight COVID-19 pandemicand bring us one step closer to overcome it. Researchers over the world areworking actively to find available alternatives in different fields, such asthe Healthcare System, pharmaceutic, health prevention, among others. With therise of artificial intelligence (AI) in the last 10 years, IA-basedapplications have become the prevalent solution in different areas because ofits higher capability, being now adopted to help combat against COVID-19. Thiswork provides a fast detection system of COVID-19 characteristics in X-Rayimages based on deep learning (DL) techniques. This system is available as afree web deployed service for fast patient classification, alleviating the highdemand for standards method for COVID-19 diagnosis. It is constituted of twodeep learning models, one to differentiate between X-Ray and non-X-Ray imagesbased on Mobile-Net architecture, and another one to identify chest X-Rayimages with characteristics of COVID-19 based on the DenseNet architecture. Forreal-time inference, it is provided a pair of dedicated GPUs, which reduce thecomputational time. The whole system can filter out non-chest X-Ray images, anddetect whether the X-Ray presents characteristics of COVID-19, highlighting themost sensitive regions.

A free web service for fast COVID-19 classification of chest X-Ray images