通过机器学习使用x射线图像进行COVID检测

Digvijay Puri, Kshamta Chauhan, P. Chauhan, Anuj Gupta
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摘要

这个电子文档是一个“活的”模板,它已经在样式表中定义了论文的组成部分[标题,正文,标题等]。由于COVID-19大流行,许多组织被迫进行重大变革,包括重新思考其业务周期的关键方面,并利用创新来履行职责,同时遵守不断变化的法规和新技术。通过使用数据框架和创新观点,该程序可以提供完整的知识,涵盖covid - 19对社会影响的兴趣点和后续影响。从当前突发事件和对这些特定地区的影响的角度,从互联网学习、人工智能、数据板、社会传播、网络安全、大信息、区块链、创新和方法论等方面对各受欢迎学科专家的观点进行了审查和交叉参考。这些观点提供了对点范围的理想理解,区分中心问题,并通过使用ML-方法利用胸部x线照片提出假设和实践建议。在本文中,使用这些ML方法来应对Covid -19大流行流情况是一个有前景的方面,正如提出的预防Covid感染模型一样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID Detection using X-Ray images through Machine Learning
This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet. Many organizations have been forced to undergo significant change as a result of the COVID-19 pandemic, including rethinking key aspects of their business cycles and utilizing innovation to stay up with duties while adhering to a shifting scene of regulations and new techniques. This procedure can offer complete knowledge covering points of interest and after effects which influence society from COVID19, by using data frameworks and innovative viewpoints. The viewpoints by various welcomed subject specialists are examined and cross referenced by internet learning, AI brainpower, data board, social communication, network safety, huge information, block chain, innovation and methodology through the perspective of the current emergency and effect on these particular regions. The viewpoints offers and ideal understanding of the scope of points, distinguishing central questions and proposals for hypothesis and practice by utilizing chest X-ray pictures using ML- approach. In the paper, the use of these ML methods to cope with the COVID-19 pandemic flow situation is a promising aspect, just as the prevention of the Covid infection model is proposed.
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