Asraf Amanullah, Islam Md Zabirul, Haque Md Rezwanul, Islam Md Milon
Department of Computer Science and Engineering, Khulna University of Engineering & Technology, Khulna, 9203 Bangladesh.
SN Comput Sci. 2020;1(6):363. doi: 10.1007/s42979-020-00383-w. Epub 2020 Nov 3.
During this global pandemic, researchers around the world are trying to find out innovative technology for a smart healthcare system to combat coronavirus. The evidence of deep learning applications on the past epidemic inspires the experts by giving a new direction to control this outbreak. The aim of this paper is to discuss the contributions of deep learning at several scales including medical imaging, disease tracing, analysis of protein structure, drug discovery, and virus severity and infectivity to control the ongoing outbreak. A progressive search of the database related to the applications of deep learning was executed on COVID-19. Further, a comprehensive review is done using selective information by assessing the different perspectives of deep learning. This paper attempts to explore and discuss the overall applications of deep learning on multiple dimensions to control novel coronavirus (COVID-19). Though various studies are conducted using deep learning algorithms, there are still some constraints and challenges while applying for real-world problems. The ongoing progress in deep learning contributes to handle coronavirus infection and plays an effective role to develop appropriate solutions. It is expected that this paper would be a great help for the researchers who would like to contribute to the development of remedies for this current pandemic in this area.
在这场全球大流行期间,世界各地的研究人员都在努力为智能医疗系统寻找创新技术,以对抗冠状病毒。过去疫情中深度学习应用的证据为专家们提供了新的方向,从而启发他们控制此次疫情爆发。本文旨在探讨深度学习在多个层面的贡献,包括医学成像、疾病追踪、蛋白质结构分析、药物发现以及病毒严重程度和传染性,以控制当前的疫情爆发。我们对与深度学习应用相关的数据库进行了逐步搜索,以查找有关COVID-19的信息。此外,通过评估深度学习的不同视角,利用筛选出的信息进行了全面综述。本文试图探索和讨论深度学习在多个维度上对控制新型冠状病毒(COVID-19)的整体应用。尽管使用深度学习算法进行了各种研究,但在应用于实际问题时仍存在一些限制和挑战。深度学习的不断进步有助于应对冠状病毒感染,并在开发适当解决方案方面发挥有效作用。预计本文将对那些希望为该领域当前大流行疾病治疗方法的开发做出贡献的研究人员有很大帮助。