Big data, artificial intelligence and epidemic disasters. A primary structured literature review

被引:0
|
作者
Lombardi, Rosa [1 ]
Trequattrini, Raffaele [2 ]
Cuozzo, Benedetta [2 ]
Manzari, Alberto [3 ]
机构
[1] Department of Law and Economics of Productive Activities, Sapienza University of Rome, Via del Castro Laurenziano 9, Rome,00161, Italy
[2] Department of Economics and Law, University of Cassino, Southern Lazio, Via S. Angelo, Loc. Folcara (FR), Cassino,03043, Italy
[3] Department of Economics, Management and Business Law, University of Bari Aldo Moro, Piazza Umberto I, 1 (BA), Bari,70121, Italy
关键词
Risk assessment - Disasters - Artificial intelligence - Disaster prevention - Decision making - Epidemiology - Big data;
D O I
暂无
中图分类号
学科分类号
摘要
This paper presents the structured literature review of the big data and artificial intelligence in relation to the epidemic disasters among which the current SAR-COV-2. Providing a deep understanding of the state of the art, the paper drafts implications and valuable insights to manage and prevent epidemic disasters by public and private organisations drafting the research agenda. Interestingly, a two-decade study of the connection between big data, artificial intelligence and pandemic or epidemic issues is undertaken for the first time. This paper adopted a longitudinal study of the literature from the relevant databases Scopus as a leading source to get access to the articles. The diffusion of epidemic disasters among which SARS-COV-2 needs to be managed investigating several aspects such as the prevention and tracking of the epidemia or pandemia. The role of smart technologies and particularly big data and artificial intelligence is useful in tracking, preventing and managing the emergency by organisations, institutions and policymakers. This study provides for the first time the connection among big data, artificial intelligence and epidemic disasters, providing valuable implications, insights and emerging issues among which the relevance of decision-making processes and risks definition and assessment. Copyright © 2022 Inderscience Enterprises Ltd.
引用
收藏
页码:156 / 180
相关论文
共 50 条
  • [41] Big data, analytics and artificial intelligence for sustainability
    Ojokoh, Bolanle A.
    Samuel, Oluwarotimi W.
    Omisore, Olatunji M.
    Sarumi, Oluwafemi A.
    Idowu, Peter A.
    Chimusa, Emile R.
    Darwish, Ashraf
    Adekoya, Adebayo F.
    Katsriku, Ferdinand A.
    SCIENTIFIC AFRICAN, 2020, 9
  • [42] BIG DATA AND ARTIFICIAL INTELLIGENCE: challenges for the Law
    Hoffmann-Riem, Wolfgang
    REVISTA ESTUDOS INSTITUCIONAIS-JOURNAL OF INSTITUTIONAL STUDIES, 2020, 6 (02): : 431 - 506
  • [43] On big data, artificial intelligence and smart cities
    Allam, Zaheer
    Dhunny, Zaynah A.
    CITIES, 2019, 89 : 80 - 91
  • [44] BIG DATA AND ARTIFICIAL INTELLIGENCE: A LOOK INTO THE FUTURE
    Longo, Giuseppe
    S&F-SCIENZAEFILOSOFIA IT, 2018, (20) : 12 - 63
  • [45] Big data and artificial intelligence in tax administration
    Oliver Cuello, Rafael
    IDP-INTERNET LAW AND POLITICS, 2021, (33):
  • [46] The power of big data and artificial intelligence in ophthalmology
    Cheng, Ching-Yu
    TAIWAN JOURNAL OF OPHTHALMOLOGY, 2023, 13 (02) : 121 - 122
  • [47] Editorial: Big data and artificial intelligence in ophthalmology
    Thakur, Sahil
    Rim, Tyler Hyungtaek
    Ting, Darren S. J.
    Hsieh, Yi-Ting
    Kim, Tae-im
    FRONTIERS IN MEDICINE, 2023, 10
  • [48] Big data and artificial intelligence in cancer research
    Wu, Xifeng
    Li, Wenyuan
    Tu, Huakang
    TRENDS IN CANCER, 2024, 10 (02) : 147 - 160
  • [49] Big data in medicine: The upcoming artificial intelligence
    Chang, Anthony C.
    PROGRESS IN PEDIATRIC CARDIOLOGY, 2016, 43 : 91 - 94
  • [50] Medical Big Data and Artificial Intelligence for Healthcare
    Zhang, Yudong
    Hong, Jin
    Chen, Shuwen
    APPLIED SCIENCES-BASEL, 2023, 13 (06):