Bibliometric top ten healthcare-related ChatGPT publications in the first ChatGPT anniversary
(2024) In Narra J 4(2).- Abstract
Since its public release on November 30, 2022, ChatGPT has shown promising potential in diverse healthcare applications despite ethical challenges, privacy issues, and possible biases. The aim of this study was to identify and assess the most influential publications in the field of ChatGPT utility in healthcare using bibliometric analysis. The study employed an advanced search on three databases, Scopus, Web of Science, and Google Scholar, to identify ChatGPT-related records in healthcare education, research, and practice between November 27 and 30, 2023. The ranking was based on the retrieved citation count in each database. The additional alternative metrics that were evaluated included (1) Semantic Scholar highly influential... (More)
Since its public release on November 30, 2022, ChatGPT has shown promising potential in diverse healthcare applications despite ethical challenges, privacy issues, and possible biases. The aim of this study was to identify and assess the most influential publications in the field of ChatGPT utility in healthcare using bibliometric analysis. The study employed an advanced search on three databases, Scopus, Web of Science, and Google Scholar, to identify ChatGPT-related records in healthcare education, research, and practice between November 27 and 30, 2023. The ranking was based on the retrieved citation count in each database. The additional alternative metrics that were evaluated included (1) Semantic Scholar highly influential citations, (2) PlumX captures, (3) PlumX mentions, (4) PlumX social media and (5) Altmetric Attention Scores (AASs). A total of 22 unique records published in 17 different scientific journals from 14 different publishers were identified in the three databases. Only two publications were in the top 10 list across the three databases. Variable publication types were identified, with the most common being editorial/commentary publications (n=8/22, 36.4%). Nine of the 22 records had corresponding authors affiliated with institutions in the United States (40.9%). The range of citation count varied per database, with the highest range identified in Google Scholar (1019–121), followed by Scopus (242–88), and Web of Science (171–23). Google Scholar citations were correlated significantly with the following metrics: Semantic Scholar highly influential citations (Spearman’s correlation coefficient ρ=0.840, p<0.001), PlumX captures (ρ=0.831, p<0.001), PlumX mentions (ρ=0.609, p=0.004), and AASs (ρ=0.542, p=0.009). In conclusion, despite several acknowledged limitations, this study showed the evolving landscape of ChatGPT utility in healthcare. There is an urgent need for collaborative initiatives by all stakeholders involved to establish guidelines for ethical, transparent, and responsible use of ChatGPT in healthcare. The study revealed the correlation between citations and alternative metrics, highlighting its usefulness as a supplement to gauge the impact of publications, even in a rapidly growing research field.
(Less)
- author
- Sallam, Malik LU
- organization
- publishing date
- 2024-08
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- bibliometric analysis, ChatGPT in healthcare, citation metric, generative AI in healthcare, publication impact
- in
- Narra J
- volume
- 4
- issue
- 2
- article number
- e917
- publisher
- Narra Sains Indonesia
- external identifiers
-
- scopus:85201063447
- pmid:39280327
- ISSN
- 2807-2618
- DOI
- 10.52225/narra.v4i2.917
- language
- English
- LU publication?
- yes
- id
- 40a68991-a6f9-4abe-89f4-bf7591716ff9
- date added to LUP
- 2025-01-08 14:52:10
- date last changed
- 2025-07-10 19:23:21
@article{40a68991-a6f9-4abe-89f4-bf7591716ff9,
abstract = {{<p>Since its public release on November 30, 2022, ChatGPT has shown promising potential in diverse healthcare applications despite ethical challenges, privacy issues, and possible biases. The aim of this study was to identify and assess the most influential publications in the field of ChatGPT utility in healthcare using bibliometric analysis. The study employed an advanced search on three databases, Scopus, Web of Science, and Google Scholar, to identify ChatGPT-related records in healthcare education, research, and practice between November 27 and 30, 2023. The ranking was based on the retrieved citation count in each database. The additional alternative metrics that were evaluated included (1) Semantic Scholar highly influential citations, (2) PlumX captures, (3) PlumX mentions, (4) PlumX social media and (5) Altmetric Attention Scores (AASs). A total of 22 unique records published in 17 different scientific journals from 14 different publishers were identified in the three databases. Only two publications were in the top 10 list across the three databases. Variable publication types were identified, with the most common being editorial/commentary publications (n=8/22, 36.4%). Nine of the 22 records had corresponding authors affiliated with institutions in the United States (40.9%). The range of citation count varied per database, with the highest range identified in Google Scholar (1019–121), followed by Scopus (242–88), and Web of Science (171–23). Google Scholar citations were correlated significantly with the following metrics: Semantic Scholar highly influential citations (Spearman’s correlation coefficient ρ=0.840, p<0.001), PlumX captures (ρ=0.831, p<0.001), PlumX mentions (ρ=0.609, p=0.004), and AASs (ρ=0.542, p=0.009). In conclusion, despite several acknowledged limitations, this study showed the evolving landscape of ChatGPT utility in healthcare. There is an urgent need for collaborative initiatives by all stakeholders involved to establish guidelines for ethical, transparent, and responsible use of ChatGPT in healthcare. The study revealed the correlation between citations and alternative metrics, highlighting its usefulness as a supplement to gauge the impact of publications, even in a rapidly growing research field.</p>}},
author = {{Sallam, Malik}},
issn = {{2807-2618}},
keywords = {{bibliometric analysis; ChatGPT in healthcare; citation metric; generative AI in healthcare; publication impact}},
language = {{eng}},
number = {{2}},
publisher = {{Narra Sains Indonesia}},
series = {{Narra J}},
title = {{Bibliometric top ten healthcare-related ChatGPT publications in the first ChatGPT anniversary}},
url = {{http://dx.doi.org/10.52225/narra.v4i2.917}},
doi = {{10.52225/narra.v4i2.917}},
volume = {{4}},
year = {{2024}},
}