This paper is in the following e-collection/theme issue:

JMIR Theme Issue: COVID-19 Special Issue (2278) Outbreak and Pandemic Preparedness and Management (1561) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1407) Epublishing and Open Access (70) Infectious Diseases (non-STD/STI) (1328) Machine Learning (1194) Digital Science, Open Science (57) Scientometrics, Infometrics, and Altmetrics (73)

Published on in Vol 23, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/23703, first published .
A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis

A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis

Authors of this article:

Alaa Abd-Alrazaq 1 Author Orcid Image ;   Jens Schneider 1 Author Orcid Image ;   Borbala Mifsud 2 Author Orcid Image ;   Tanvir Alam 1 Author Orcid Image ;   Mowafa Househ 1 Author Orcid Image ;   Mounir Hamdi 1 Author Orcid Image ;   Zubair Shah 1 Author Orcid Image
Article Authors Cited by (23) Tweetations (12) Metrics

Journals

  1. Kumar V, Singh D, Kaur M, Damaševičius R. Overview of current state of research on the application of artificial intelligence techniques for COVID-19. PeerJ Computer Science 2021;7:e564 View
  2. Teixeira da Silva J. Non-compliance with ethical rules caused by misuse of ORCID accounts: Implications for medical publications in the COVID-19 era. Ethics, Medicine and Public Health 2021;18:100692 View
  3. Adadi A, Lahmer M, Nasiri S. Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead. Journal of King Saud University - Computer and Information Sciences 2022;34(8):5898 View
  4. Kaul V, Chahal J, Schrarstzhaupt I, Geduld H, Shen Y, Cecconi M, Siqueira A, Markoski M, Kawano-Dourado L. Lessons Learned from a Global Perspective of Coronavirus Disease-2019. Clinics in Chest Medicine 2023;44(2):435 View
  5. Klingelhöfer D, Braun M, Brüggmann D, Groneberg D. The Pandemic Year 2020: World Map of Coronavirus Research. Journal of Medical Internet Research 2021;23(9):e30692 View
  6. Al-Ryalat N, Malkawi L, Abu Salhiyeh A, Abualteen F, Abdallah G, Al Omari B, AlRyalat S. Radiology During the COVID-19 Pandemic: Mapping Radiology Literature in 2020. Current Medical Imaging Reviews 2023;19(2):175 View
  7. de Vries R, Thielmann I. COVID-19 vermijdingsgedrag: Het belang van persoonlijkheid en de relatie met toename in thuiswerken. Gedrag & Organisatie 2021;34(4) View
  8. Cheng X, Tang L, Zhou M, Wang G. Coevolution of COVID-19 research and China’s policies. Health Research Policy and Systems 2021;19(1) View
  9. Wang Z, Sun Y, Shen R, Tang X, Xu Y, Zhang Y, Liu Y. Global scientific trends on the immunomodulation of mesenchymal stem cells in the 21st century: A bibliometric and visualized analysis. Frontiers in Immunology 2022;13 View
  10. Rostami S, Gharibi S, Yaghoobi H, Nokhodian Z, Shoaei P, Bahrami A, Ahangarzadeh S, Alibakhshi A. Herbal Medicines as Potential Inhibitors of SARS-CoV-2 Infection. Current Pharmaceutical Design 2022;28(29):2375 View
  11. Oyewola D, Dada E. Exploring machine learning: a scientometrics approach using bibliometrix and VOSviewer. SN Applied Sciences 2022;4(5) View
  12. OYEWOLA D, DADA E. Scientometric Analysis of COVID-19 Scholars Publication using Machine Learning. International Journal of Applied Mathematics Electronics and Computers 2022;10(1):1 View
  13. McNally E, Elkind M, Benjamin I, Chung M, Dillon G, Hernandez A, Ibeh C, Lloyd-Jones D, McCullough L, Wold L, Wright D, Wu J. Impact of the COVID-19 Pandemic on Cardiovascular Science: Anticipating Problems and Potential Solutions: A Presidential Advisory From the American Heart Association. Circulation 2021;144(23) View
  14. Chicaiza J, Villota S, Vinueza-Naranjo P, Rumipamba-Zambrano R. Contribution of Deep-Learning Techniques Toward Fighting COVID-19: A Bibliometric Analysis of Scholarly Production During 2020. IEEE Access 2022;10:33281 View
  15. Park S, Lim H, Park J, Choe Y. Impact of COVID-19 Pandemic on Biomedical Publications and Their Citation Frequency. Journal of Korean Medical Science 2022;37(40) View
  16. García-Pascual V, García-Beltrán E, Domenech-Amigot B. Eye-Related COVID-19: A Bibliometric Analysis of the Scientific Production Indexed in Scopus. International Journal of Environmental Research and Public Health 2022;19(16):9927 View
  17. Magazzino C, Mele M, Coccia M. A machine learning algorithm to analyse the effects of vaccination on COVID-19 mortality. Epidemiology and Infection 2022;150 View
  18. Sheu R, Chen L, Wu C, Pardeshi M, Pai K, Huang C, Chen C, Chen W. Multi-Modal Data Analysis for Pneumonia Status Prediction Using Deep Learning (MDA-PSP). Diagnostics 2022;12(7):1706 View
  19. Rabby G, D’Souza J, Oelen A, Dvorackova L, Svátek V, Auer S. Impact of COVID-19 research: a study on predicting influential scholarly documents using machine learning and a domain-independent knowledge graph. Journal of Biomedical Semantics 2023;14(1) View

Books/Policy Documents

  1. Achalla M, Muniraju G, Banavar M, Tepedelenlioglu C, Spanias A, Schuckers S. Studies to Combat COVID-19 using Science and Engineering. View
  2. Marques J, Fong S, Li G, Arraut I, Gois F, Neto J. Epidemic Analytics for Decision Supports in COVID19 Crisis. View
  3. Agjei R, Adusei-Mensah F, Balogun O, Olaleye S. Intelligent Systems Design and Applications. View