Artificial Intelligence Driven Bibliometric Insights: Pioneering Down Syndrome Research

Shabana Shafi; Aijaz Ahmad Reshi; Arif Shah; Reem Hamad Al-Mutairi; Gharam Naif Al-Mutairi; Ajaz Ahmad

doi:10.52756/ijerr.2024.v37spl.006

Authors

Shabana Shafi Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia
Aijaz Ahmad Reshi Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia https://orcid.org/0000-0002-0795-2835
Arif Shah Department of Management, OPJS University, Rajasthan, India
Reem Hamad Al-Mutairi Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia
Gharam Naif Al-Mutairi Department of Computer Science, College of Computer Science and Engineering, Taibah University, Madinah, Saudi Arabia
Ajaz Ahmad Departments of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia https://orcid.org/0000-0001-6295-8685

DOI:

https://doi.org/10.52756/ijerr.2024.v37spl.006

Abstract

The present bibliometric analysis investigates the scholarly output from 2013 to 2022 to explore the use of artificial intelligence (AI) in Down syndrome research. The analysis demonstrates a significant and rapid growth in publications, starting from a minimal number of 17 articles in 2013 and reaching a peak of 2162 by 2022. This indicates a notable increase in interest and dedication to this topic. Upon analyzing national contributions, the United States stands up as a frontrunner in terms of research output, citations, and collaborations. This underscores its crucial role in influencing the discussion and influence of AI-driven Down syndrome research. The dynamics of collaboration, especially between the United States and countries like the United Kingdom, China, and Germany, illustrate a vast worldwide network that facilitates the exchange of information. The congruence of these findings with past research highlights the regularity in exponential growth tendencies, which can be attributed to technical discoveries and interdisciplinary cooperation. Moreover, the prevalence of dominant nations, the significance of renowned publications, and the sway of prolific authors underscore the firmly established connections between research productivity and influence within specific fields of study. The study's findings suggest that future developments in AI-driven Down syndrome research will focus on integrating AI more deeply, fostering interdisciplinary collaborations, and prioritizing ethical considerations. These trends align with the anticipated paths and ethical obligations in this field.

Keywords: Artificial intelligence; Bibliometric Analysis; Down syndrome

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