A bibliometric analysis of the advance of artificial intelligence in medicine

作者：Mian Lin, Lingzhi Lin, Lingling Lin, Zhengqiu Lin, Xiaoxiao Yan · 发表于：Frontiers in Medicine · 年份：2025 · DOI：10.3389/fmed.2025.1504428 · 被引用次数：30 · 研究领域：Artificial Intelligence in Healthcare and Education、COVID-19 diagnosis using AI、Machine Learning in Healthcare

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...