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

被引:3
作者
Pillai, Sini, V [1 ]
Kumar, Ranjith S. [2 ]
机构
[1] CET Sch Management, Coll Engn Trivandrum, Thiruvananthapuram 695016, Kerala, India
[2] Coll Engn Trivandrum, Dept Mech Engn, Micro Nanofluid Res Lab, Thiruvananthapuram 695016, Kerala, India
关键词
Data analytics; Data-driven decision; Artificial intelligence; Deep learning; Machine learning; AI; HEALTH;
D O I
10.1007/s40622-021-00289-3
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
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:15
相关论文
共 77 条
  • [1] Artificial intelligence and COVID-19: A multidisciplinary approach
    Ahuja, Abhimanyu S.
    Reddy, Vineet Pasam
    Marques, Oge
    [J]. INTEGRATIVE MEDICINE RESEARCH, 2020, 9 (03)
  • [2] Al-Timemy AH, 2020, ARXIV PREPRINT ARXIV
  • [3] On the Coronavirus (COVID-19) Outbreak and the Smart City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence (AI) to Benefit Urban Health Monitoring and Management
    Allam, Zaheer
    Jones, David S.
    [J]. HEALTHCARE, 2020, 8 (01)
  • [4] Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population
    Banerjee, Abhirup
    Ray, Surajit
    Vorselaars, Bart
    Kitson, Joanne
    Mamalakis, Michail
    Weeks, Simonne
    Baker, Mark
    Mackenzie, Louise S.
    [J]. INTERNATIONAL IMMUNOPHARMACOLOGY, 2020, 86
  • [5] Beard S, 2020, DATA GOVERNANCE ISSU
  • [6] Going viral - Covid-19 impact assessment: A perspective beyond clinical practice
    Bobdey, Saurabh
    Ray, Sougat
    [J]. JOURNAL OF MARINE MEDICAL SOCIETY, 2020, 22 (01) : 9 - 12
  • [7] Bullock J, 2020, J ARTIF INTELL RES, V69, P807
  • [8] A Comprehensive Review of the COVID-19 Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Impact
    Chamola, Vinay
    Hassija, Vikas
    Gupta, Vatsal
    Guizani, Mohsen
    [J]. IEEE ACCESS, 2020, 8 : 90225 - 90265
  • [9] Artificial Intelligence for COVID-19: Rapid Review
    Chen, Jiayang
    See, Kay Choong
    [J]. JOURNAL OF MEDICAL INTERNET RESEARCH, 2020, 22 (10)
  • [10] Fangcang shelter hospitals: a novel concept for responding to public health emergencies
    Chen, Simiao
    Zhang, Zongjiu
    Yang, Juntao
    Wang, Jian
    Zhai, Xiaohui
    Barnighausen, Till
    Wang, Chen
    [J]. LANCET, 2020, 395 (10232) : 1305 - 1314