The crisis generated on the planet by COVID-19 (SARS-CoV-2) caused a devastating effect worldwide, and for this reason, an effective detection of the possible contagion of infected patients was needed. In this sense, the present work gathers information from diagnostic tools that use Deep Learning (DL) in medical images to detect COVID-19. It is a descriptive observational study. In addition, the purpose of this study is to analyze and compare how DL applied to radiographic images optimizes resources and management of results in an objective and timely manner, showing a favorable cooperation between the health, institutional and technological sectors. In such a way that Convolutional Neural Networks (CNN) in their different algorithms are the chosen architecture in the biomedical area for the diagnosis of diseases applied to the analysis of radiographic images, which purpose is to help t...