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A Comprehensive Study of Artificial Intelligence and Machine Learning Approaches in Confronting the Coronavirus (COVID-19) Pandemic.

  • Rahman, Md Mijanur1
  • Khatun, Fatema2
  • Uzzaman, Ashik1
  • Sami, Sadia Islam1
  • Bhuiyan, Md Al-Amin3
  • Kiong, Tiong Sieh4
  • 1 421983Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, Bangladesh. , (Bangladesh)
  • 2 421965Bangabandhu Sheikh Mujibur Rahman Science & Technology University, Gopalganj, Dhaka, Bangladesh. , (Bangladesh)
  • 3 114800King Faisal University, Hofuf, Al Ahsa, Saudi Arabia. , (Saudi Arabia)
  • 4 65292Universiti Tenaga Nasional (UNITEN), Kajang, Selangor, Malaysia. , (Malaysia)
Published Article
International journal of health services : planning, administration, evaluation
Publication Date
May 17, 2021
DOI: 10.1177/00207314211017469
PMID: 33999732


The novel coronavirus disease (COVID-19) has spread over 219 countries of the globe as a pandemic, creating alarming impacts on health care, socioeconomic environments, and international relationships. The principal objective of the study is to provide the current technological aspects of artificial intelligence (AI) and other relevant technologies and their implications for confronting COVID-19 and preventing the pandemic's dreadful effects. This article presents AI approaches that have significant contributions in the fields of health care, then highlights and categorizes their applications in confronting COVID-19, such as detection and diagnosis, data analysis and treatment procedures, research and drug development, social control and services, and the prediction of outbreaks. The study addresses the link between the technologies and the epidemics as well as the potential impacts of technology in health care with the introduction of machine learning and natural language processing tools. It is expected that this comprehensive study will support researchers in modeling health care systems and drive further studies in advanced technologies. Finally, we propose future directions in research and conclude that persuasive AI strategies, probabilistic models, and supervised learning are required to tackle future pandemic challenges.

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