Artículo

The Research Interest in ChatGPT and Other Natural Language Processing Tools from a Public Health Perspective: A Bibliometric Analysis

Resumen

Background: Natural language processing, such as ChatGPT, demonstrates growing potential across numerous research scenarios, also raising interest in its applications in public health and epidemiology. Here, we applied a bibliometric analysis for a systematic assessment of the current literature related to the applications of ChatGPT in epidemiology and public health. Methods: A bibliometric analysis was conducted on the Biblioshiny web-app, by collecting original articles indexed in the Scopus database between 2010 and 2023. Results: On a total of 3431 original medical articles, “Article” and “Conference paper”, mostly constituting the total of retrieved documents, highlighting that the term “ChatGPT” becomes an interesting topic from 2023. The annual publications escalated from 39 in 2010 to 719 in 2023, with an average annual growth rate of 25.1%. In terms of country production over time, the USA led with the highest overall production from 2010 to 2023. Concerning citations, the most frequently cited countries were the USA, UK, and China. Interestingly, Harvard Medical School emerges as the leading contributor, accounting for 18% of all articles among the top ten affiliations. Conclusions: Our study provides an overall examination of the existing research interest in ChatGPT’s applications for public health by outlining pivotal themes and uncovering emerging trends.
Chavez, Henry (57213581521); Albornoz, María Belén (57192277503); Martín, Fernando (57746138000)
‘Big data’ Research: A Bibliometric Analysis of the Scopus Database, 2009-2019
2022
10.5530/jscires.11.1.7
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132106342&doi=10.5530%2fjscires.11.1.7&partnerID=40&md5=94cfb7404692c0b2ce9373f1b3b2d931
All Open Access; Hybrid Gold Open Access
Scopus
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