Alafif Tarik, Tehame Abdul Muneeim, Bajaba Saleh, Barnawi Ahmed, Zia Saad
Computer Science Department, Jamoum University College, Umm Al-Qura University, Jamoum 25375, Saudi Arabia.
Department of Software Engineering, Sir Syed University of Engineering and Technology, Karachi 75300, Pakistan.
Int J Environ Res Public Health. 2021 Jan 27;18(3):1117. doi: 10.3390/ijerph18031117.
With many successful stories, machine learning (ML) and deep learning (DL) have been widely used in our everyday lives in a number of ways. They have also been instrumental in tackling the outbreak of Coronavirus (COVID-19), which has been happening around the world. The SARS-CoV-2 virus-induced COVID-19 epidemic has spread rapidly across the world, leading to international outbreaks. The COVID-19 fight to curb the spread of the disease involves most states, companies, and scientific research institutions. In this research, we look at the Artificial Intelligence (AI)-based ML and DL methods for COVID-19 diagnosis and treatment. Furthermore, in the battle against COVID-19, we summarize the AI-based ML and DL methods and the available datasets, tools, and performance. This survey offers a detailed overview of the existing state-of-the-art methodologies for ML and DL researchers and the wider health community with descriptions of how ML and DL and data can improve the status of COVID-19, and more studies in order to avoid the outbreak of COVID-19. Details of challenges and future directions are also provided.
凭借众多成功案例,机器学习(ML)和深度学习(DL)已在诸多方面广泛应用于我们的日常生活。它们在应对全球范围内爆发的新型冠状病毒(COVID - 19)疫情中也发挥了重要作用。严重急性呼吸综合征冠状病毒2(SARS-CoV-2)引发的COVID - 19疫情已在全球迅速蔓延,导致国际范围内的疫情爆发。抗击COVID - 19以遏制疾病传播涉及大多数国家、公司和科研机构。在本研究中,我们探讨基于人工智能(AI)的机器学习和深度学习方法用于COVID - 19的诊断和治疗。此外,在抗击COVID - 19的战斗中,我们总结了基于人工智能的机器学习和深度学习方法以及可用的数据集、工具和性能。本综述为机器学习和深度学习研究人员以及更广泛的健康领域提供了现有最先进方法的详细概述,描述了机器学习、深度学习和数据如何改善COVID - 19的状况,以及为避免COVID - 19爆发而进行的更多研究。还提供了挑战细节和未来方向。