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Covid-19’s Rapid diagnosis Open platform based on X-Ray Imaging and Deep Learning

机译:Covid-19基于X射线成像和深度学习的快速诊断开放平台

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The Coronavirus epidemic first appeared in Wuhan-China on December, 31st, 2019. This has put the world’s hospitals, clinics, testing laboratories and health administrations under pressure. As of April, 04th, 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.
机译:冠状病毒流行病首先出现在2019年12月31日的武汉 - 中国。这使世界医院,诊所,检测实验室和卫生主管部门在压力下。截至2020年4月4日,世界卫生组织报告了超过167515年在全球100多个国家的确认案件。疫情的诊断将增加对负担过重测试实验室的负担。已经并行提出了几种筛选方法,以便于促进,并且最重要的是,更容易地快速诊断。在这个级别,X射线图像似乎是新兴国家有助于快速筛查的良好解决方案。本文提出的解决方案包括基于卷积神经网络的协作和智能平台,用于分类和检测即VGG16。该平台可确保X射线图像的快速下载,随后将患者的个人信息输入,然后启动5秒测试。因此,该平台产生包含所有患者信息的PDF文件。

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