The role of data-driven artificial intelligence on COVID-19 disease management in public sphere: a review

被引:0
作者
Sini V. Pillai
Ranjith S. Kumar
机构
[1] CET School of Management,College of Engineering Trivandrum
[2] College of Engineering Trivandrum,Micro/Nanofluidics Research Laboratory, Department of Mechanical Engineering
来源
DECISION | 2021年 / 48卷
关键词
Data analytics; Data-driven decision; Artificial intelligence; Deep learning; Machine learning;
D O I
暂无
中图分类号
学科分类号
摘要
Coronavirus disease 2019 (COVID-19) is an infectious disease with acute intense respiratory syndrome which spread around the world for the very first time impacting the way of life with drastic uncertainty. It rapidly reached almost every nook and corner of the world and the World Health Organization (WHO) has announced COVID-19 as a pandemic. The health care institutions around the globe are looking for viable and real-time technological solutions to handle the virus for evading its spread and circumvent probable demises. Importantly, the artificial intelligence tools and techniques are playing a major role in fighting the effect of virus on the economic jolt by mimicking human intelligence by screening, analyzing, predicting and tracking the existing and likely future patients. Since the first reported case, all the government organizations in the world jumped into action to prevent it and many studies reported the role of AI in taking decisions analyzing big data available in public sphere. Thereby, this review focuses on identifying the significant implication of AI techniques used for the COVID-19 disease management in the public sphere by agglomerating the latest available information. It also discusses the pitfalls and future directions in handling sensitive big data required for advanced neural networks.
引用
收藏
页码:375 / 389
页数:14
相关论文
共 117 条
  • [1] Bobdey S(2020)Going viral–covid-19 impact assessment: a perspective beyond clinical practice J Mar Med Soc 22 9-90265
  • [2] Ray S(2020)A comprehensive review of the covid-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact IEEE Access 8 90225-1246
  • [3] Chamola Vinay(2020)Artificial intelligence for covid-19: rapid review J Med Internet Res 22 e21476-2282
  • [4] Hassija Vikas(2020)Strong social distancing measures in the united states reduced the covid-19 growth rate: study evaluates the impact of social distancing measures on the growth rate of confirmed covid-19 cases across the united states Health Aff 39 1237-36
  • [5] Gupta Vatsal(2020)An agent-based model to evaluate the COVID-19 transmission risks in facilities Comput Biol Med 121 103827-132
  • [6] Guizani Mohsen(2020)Impact of covid-19 pandemic on information management research and practice: transforming education, work and life Int J Inf Manag 55 102211-266
  • [7] Chen J(2019)Artificial intelligence in health care: will the value match the hype? Jama 321 2281-464
  • [8] See KC(2020)A case for participatory disease surveillance of the covid-19 pandemic in india JMIR Public Health Surveill 6 e18795-493
  • [9] Courtemanche C(2019)The practical implementation of artificial intelligence technologies in medicine Nat Med 25 30-60
  • [10] Garuccio J(2020)Explainable AI and mass surveillance system-based healthcare framework to combat covid-i9 like pandemics IEEE Netw 34 126-21