Mapping Key Nodes and Global Trends in AI and Large Language Models for Medical Education: A Bibliometric Study. Article Swipe

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Kaining Lu , Shengxiang Sun , Wanzhang Liu , Jiao Jiang , Zejun Yan ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.2147/amep.s538362

AI and LLMs in medical education constitute a fast-evolving field, with journal calls shaping its bibliometric landscape and advancing the discipline. The field remains in a developmental phase, with subfields yet to be clearly defined. Topics such as nursing education, digital health, medical examinations, and conversational agents are gaining traction. Research on ChatGPT and LLMs holds a central and influential role. Emerging areas of focus include medical ethics, training methodologies, and skills development. Clinical reasoning, undergraduate education, and virtual reality in AI and LLMs for medical education are understudied, offering research opportunities.

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Key (lock) Data science Computer science MEDLINE Bibliometrics Information retrieval Library science Biology Computer security Biochemistry

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Type: article
Language: en
Landing Page: https://pubmed.ncbi.nlm.nih.gov/40832621
OA Status: green
Cited By: 1
Related Works: 10
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DOI: https://doi.org/10.2147/amep.s538362

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Title: Mapping Key Nodes and Global Trends in AI and Large Language Models for Medical Education: A Bibliometric Study.

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Language: en

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Publication year: 2025

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Publication date: 2025-01-01

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Authors: Kaining Lu, Shengxiang Sun, Wanzhang Liu, Jiao Jiang, Zejun Yan

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Landing page: https://pubmed.ncbi.nlm.nih.gov/40832621

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OA URL: https://www.ncbi.nlm.nih.gov/pmc/articles/12360372

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Concepts: Key (lock), Data science, Computer science, MEDLINE, Bibliometrics, Information retrieval, Library science, Biology, Computer security, Biochemistry

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Cited by: 1

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