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Cited by 14Artificial Intelligence in Healthcare and Educationscientometrics and bibliometrics researchDiverse Approaches in Healthcare and Education Studies

Global trends and hotspots of ChatGPT in medical research: a bibliometric and visualized study

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Liu, Ling, Qu, Shenhong, Zhao, Haiyun, Kong, Lingping, Xie, Zhuzhu, Jiang, Zhichao, Zou, Pan·2024·Frontiers in Medicine
DOI 10.3389/fmed.2024.1406842PMC PMC11137200
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Abstract

Objective: With the rapid advancement of Chat Generative Pre-Trained Transformer (ChatGPT) in medical research, our study aimed to identify global trends and focal points in this domain. Method: All publications on ChatGPT in medical research were retrieved from the Web of Science Core Collection (WoSCC) by Clarivate Analytics from January 1, 2023, to January 31, 2024. The research trends and focal points were visualized and analyzed using VOSviewer and CiteSpace. Results: A total of 1,239 publications were collected and analyzed. The USA contributed the largest number of publications (458, 37.145%) with the highest total citation frequencies (2,461) and the largest H -index. Harvard University contributed the highest number of publications (33) among all full-time institutions. The Cureus Journal of Medical Science published the most ChatGPT-related research (127, 10.30%). Additionally, Wiwanitkit V contributed the majority of publications in this field (20). “Artificial Intelligence (AI) and Machine Learning (ML),” “Education and Training,” “Healthcare Applications,” and “Data Analysis and Technology” emerged as the primary clusters of keywords. These areas are predicted to remain hotspots in future research in this field. Conclusion: Overall, this study signifies the interdisciplinary nature of ChatGPT research in medicine, encompassing AI and ML technologies, education and training initiatives, diverse healthcare applications, and data analysis and technology advancements. These areas are expected to remain at the forefront of future research, driving continued innovation and progress in the field of ChatGPT in medical research.

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  • LLMs represent a rapidly emerging research paradigm in diabetic complication prediction.

    “Currently, LLMs represent a rapidly emerging research paradigm in diabetic complication prediction, with growing studies exploring their potential lies in processing unstructured clinical text [169], enabling personalized health management via conversational agents [170], and supporting biomedical knowledge discovery [171].”

    From Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics (2026) · cites this paper as [170]

    The Introduction (page unavailable) says ChatGPT can analyze medical records and clinical notes and extract insights from unstructured text, supporting the application nearest citation [169]. The Discussion describes rapid uptake of LLMs in medicine, but the paper does not establish an emerging research paradigm specifically in diabetic complication prediction. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Liu, L., Qu, S., Zhao, H., Kong, L., Xie, Z., Jiang, Z., & Zou, P.
Affiliations
  • Hunan University of Traditional Chinese Medicine (CN)
  • The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
  • Second People Hospital of Hunan (CN)
Corresponding author
Zou, Pan
ORCID
Venue
Frontiers in Medicine
Publisher
Frontiers Media SA
Published
2024-05-16
Volume
11
Pages
1406842-1406842
ISSN
2296-858X (ISSN-L)
DOI
10.3389/fmed.2024.1406842
PMC
PMC11137200
OpenAlex
W4396972428
Cited by
14
References
13
Citations by year
2026: 5 · 2025: 7 · 2024: 2
FWCI
1.31
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Diverse Approaches in Healthcare and Education Studies
Keywords
ChatGPT, large language models, medical research, research trends, research hotspots, artificial intelligence in healthcare, machine learning, medical education, medical applications, research collaboration

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