ML Based Hybrid Approach for COVID Disease Detection Using X-Ray Images

P. Gupta, Anuj Gupta, Digvijay Puri
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Abstract

The COVID-19 epidemic has forced several organizations to undergo major shift, to examine essential aspects of their economic cycles and to make use of invention to maintain activities whilst maintaining a shifting rule scene and unique method. This review provides a comprehensive understanding via a framework of facts and an original approach of huge no of key issues and fundamental subtleties impacting organizations and society from COVID-19. The views for different welcoming industry professionals are analyzed and broken down when the specific interpretations may be understood Web learning, modern technology, man-made brainpower, data board, social communication, security of networks, information giant, blockchain, security, multi-faceted invention and approach from the present emergency standpoint and influence on such specific areas. The master perspectives give the extent of the elements optimum comprehension, distinguishing central questions and proposals for hypothesis and practice by utilizing chest X-Ray pictures with 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 Covid infection model is proposed. Result shows the proposed hybrid approach gives better accuracy as compared to other
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基于ML的基于x射线图像的COVID疾病检测混合方法
2019冠状病毒病疫情迫使一些组织进行重大转变,审查其经济周期的重要方面,并利用发明来维持活动,同时保持不断变化的规则场景和独特的方法。这篇综述通过事实框架和原创方法,提供了对COVID-19影响组织和社会的大量关键问题和基本微妙之处的全面理解。从当前应急的角度出发,对网络学习、现代技术、人工智能、数据板、社交通信、网络安全、信息巨头、区块链、安全、多方面的发明和方法以及对这些特定领域的影响等具体解读,分析和分解了不同欢迎行业专业人士的观点。主视角给出了元素的最佳理解程度,区分中心问题和建议的假设和实践,利用胸部x线照片与ML方法。在本文中,使用这些ML方法来应对Covid -19大流行的流量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。结果表明,与其他方法相比,所提出的混合方法具有更好的精度
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