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医学领域人工智能进展的文献计量分析

A bibliometric analysis of the advance of artificial intelligence in medicine.

作者信息

Lin Mian, Lin Lingzhi, Lin Lingling, Lin Zhengqiu, Yan Xiaoxiao

机构信息

Department of Orthopedics, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Department of Neurology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

出版信息

Front Med (Lausanne). 2025 Feb 21;12:1504428. doi: 10.3389/fmed.2025.1504428. eCollection 2025.

Abstract

INTRODUCTION

The integration of artificial intelligence (AI) into medicine has ushered an era of unprecedented innovation, with substantial impacts on healthcare delivery and patient outcomes. Understanding the current development, primary research focuses, and key contributors in AI applications in medicine through bibliometric analysis is essential.

METHODS

For this research, we utilized the Web of Science Core Collection as our main database and performed a review of literature covering the period from January 2019 to December 2023. VOSviewer and R-bibliometrix were performed to conduct bibliometric analysis and network visualization, including the number of publications, countries, journals, citations, authors, and keywords.

RESULTS

A total of 1,811 publications on research for AI in medicine were released across 565 journals by 12,376 authors affiliated with 3,583 institutions from 97 countries. The United States became the foremost producer of scholarly works, significantly impacting the field. Harvard Medical School exhibited the highest publication count among all institutions. The Journal of Medical Internet Research achieved the highest H-index (19), publication count (76), and total citations (1,495). Four keyword clusters were identified, covering AI applications in digital health, COVID-19 and ChatGPT, precision medicine, and public health epidemiology. "Outcomes" and "Risk" demonstrated a notable upward trend, indicating the utilization of AI in engaging with clinicians and patients to discuss patients' health condition risks, foreshadowing future research focal points.

CONCLUSION

Analyzing our bibliometric data allowed us to identify progress, focus areas, and emerging fields in AI for medicine, pointing to potential future research directions. Since 2019, there has been a steady rise in publications related to AI in medicine, indicating its rapid growth. In addition, we reviewed journals and significant publications to pinpoint prominent countries, institutions, and academics. Researchers will gain important insights into the current landscape, collaborative frameworks, and key research topics in the field from this study. The findings suggest directions for future research.

摘要

引言

人工智能(AI)融入医学开创了一个前所未有的创新时代,对医疗服务提供和患者治疗结果产生了重大影响。通过文献计量分析了解AI在医学应用中的当前发展、主要研究重点和关键贡献者至关重要。

方法

本研究以Web of Science核心合集作为主要数据库,对2019年1月至2023年12月期间的文献进行综述。使用VOSviewer和R-bibliometrix进行文献计量分析和网络可视化,包括出版物数量、国家、期刊、引用、作者和关键词。

结果

来自97个国家3583个机构的12376名作者在565种期刊上发表了共计1811篇关于医学AI研究的论文。美国成为学术著作的主要产出国,对该领域产生了重大影响。哈佛医学院在所有机构中发表论文数量最多。《医学互联网研究杂志》的H指数最高(19)、发表论文数量最多(76)、总引用次数最多(1495)。确定了四个关键词聚类,涵盖AI在数字健康、新冠疫情与ChatGPT、精准医学以及公共卫生流行病学方面的应用。“结果”和“风险”呈现出显著的上升趋势,表明AI在与临床医生和患者讨论患者健康状况风险方面的应用,预示着未来的研究重点。

结论

通过分析我们的文献计量数据,我们能够确定医学AI的进展、重点领域和新兴领域,指明未来潜在的研究方向。自2019年以来,医学领域与AI相关的出版物稳步增加,表明其快速发展。此外,我们审查了期刊和重要出版物,以确定突出的国家、机构和学者。研究人员将从本研究中深入了解该领域的当前状况、合作框架和关键研究主题。研究结果为未来研究指明了方向。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a5/11885233/042c5511999b/fmed-12-1504428-g001.jpg

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