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Publication Trends and Hot Spots of ChatGPT's Application in the Medicine.
Li, Zhi-Qiang; Wang, Xue-Feng; Liu, Jian-Ping.
Afiliação
  • Li ZQ; Centre for Evidence-based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
  • Wang XF; Centre for Evidence-based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
  • Liu JP; Centre for Evidence-based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China. liujp@bucm.edu.cn.
J Med Syst ; 48(1): 52, 2024 May 18.
Article em En | MEDLINE | ID: mdl-38761230
ABSTRACT
This study aimed to analyze the current landscape of ChatGPT application in the medical field, assessing the current collaboration patterns and research topic hotspots to understand the impact and trends. By conducting a search in the Web of Science, we collected literature related to the applications of ChatGPT in medicine, covering the period from January 1, 2000 up to January 16, 2024. Bibliometric analyses were performed using CiteSpace (V6.2., Drexel University, PA, USA) and Microsoft Excel (Microsoft Corp.,WA, USA) to map the collaboration among countries/regions, the distribution of institutions and authors, and clustering of keywords. A total of 574 eligible articles were included, with 97.74% published in 2023. These articles span various disciplines, particularly in Health Care Sciences Services, with extensive international collaboration involving 73 countries. In terms of countries/regions studied, USA, India, and China led in the number of publications. USA ot only published nearly half of the total number of papers but also exhibits a highest collaborative capability. Regarding the co-occurrence of institutions and scholars, the National University of Singapore and Harvard University held significant influence in the cooperation network, with the top three authors in terms of publications being Wiwanitkit V (10 articles), Seth I (9 articles), Klang E (7 articles), and Kleebayoon A (7 articles). Through keyword clustering, the study identified 9 research theme clusters, among which "digital health"was not only the largest in scale but also had the most citations. The study highlights ChatGPT's cross-disciplinary nature and collaborative research in medicine, showcasing its growth potential, particularly in digital health and clinical decision support. Future exploration should examine the socio-economic and cultural impacts of this trend, along with ChatGPT's specific technical uses in medical practice.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Bibliometria Idioma: En Revista: J Med Syst Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Bibliometria Idioma: En Revista: J Med Syst Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China