Department of Computer Engineering, Istanbul Aydin University, Istanbul, 34295, Turkey.
Department of Computer Engineering, Istanbul Sabahattin Zaim University, Istanbul, 34303, Turkey.
Interdiscip Sci. 2021 Jun;13(2):153-175. doi: 10.1007/s12539-021-00431-w. Epub 2021 Apr 22.
The recent COVID-19 pandemic, which broke at the end of the year 2019 in Wuhan, China, has infected more than 98.52 million people by today (January 23, 2021) with over 2.11 million deaths across the globe. To combat the growing pandemic on urgent basis, there is need to design effective solutions using new techniques that could exploit recent technology, such as machine learning, deep learning, big data, artificial intelligence, Internet of Things, for identification and tracking of COVID-19 cases in near real time. These technologies have offered inexpensive and rapid solution for proper screening, analyzing, prediction and tracking of COVID-19 positive cases. In this paper, a detailed review of the role of AI as a decisive tool for prognosis, analyze, and tracking the COVID-19 cases is performed. We searched various databases including Google Scholar, IEEE Library, Scopus and Web of Science using a combination of different keywords consisting of COVID-19 and AI. We have identified various applications, where AI can help healthcare practitioners in the process of identification and monitoring of COVID-19 cases. A compact summary of the corona virus cases are first highlighted, followed by the application of AI. Finally, we conclude the paper by highlighting new research directions and discuss the research challenges. Even though scientists and researchers have gathered and exchanged sufficient knowledge over last couple of months, but this structured review also examined technological perspectives while encompassing the medical aspect to help the healthcare practitioners, policymakers, decision makers, policymakers, AI scientists and virologists to quell this infectious COVID-19 pandemic outbreak.
截至 2021 年 1 月 23 日，全球范围内，由 2019 年末在中国武汉爆发的新冠肺炎疫情已感染超过 9852 万人，造成超过 211 万人死亡。为了在紧急情况下应对不断蔓延的疫情，我们需要利用新的技术设计有效的解决方案，例如机器学习、深度学习、大数据、人工智能、物联网等，以便实时识别和追踪新冠肺炎病例。这些技术为新冠肺炎阳性病例的正确筛查、分析、预测和跟踪提供了廉价而快速的解决方案。本文详细回顾了人工智能作为新冠肺炎预后、分析和追踪的决策工具的作用。我们使用了不同的关键词组合，包括 COVID-19 和 AI，在包括 Google Scholar、IEEE 图书馆、Scopus 和 Web of Science 在内的各种数据库中进行了搜索。我们已经确定了人工智能可以帮助医疗保健从业者识别和监测新冠肺炎病例的各种应用。首先突出显示了冠状病毒病例的简要摘要，然后介绍了人工智能的应用。最后，我们通过突出新的研究方向并讨论研究挑战来结束本文。尽管科学家和研究人员在过去几个月中已经收集和交流了足够的知识，但本综述还从技术角度考察了这一问题，以帮助医疗保健从业者、政策制定者、决策者、人工智能科学家和病毒学家控制这一传染性的新冠肺炎疫情爆发。
