This scholarly article, “A bibliometric analysis of the advance of artificial intelligence in medicine,” authored by Mian Lin, Lingzhi Lin, Lingling Lin, Zhengqiu Lin, and Xiaoxiao Yan, was published on February 21, 2025, in Frontiers in Medicine, Volume 12, Article 1504428.
The paper’s primary objective is to provide a comprehensive understanding of the current development, principal research foci, and key contributors within the field of artificial intelligence (AI) applications in medicine. It emphasizes that AI’s integration has initiated an era of significant innovation, profoundly impacting healthcare delivery and patient outcomes. The research specifically investigates article characteristics on AI in medicine over the past 5 years, reflecting a growing interest in this domain.
To achieve this, the authors conducted a bibliometric analysis using the Web of Science Core Collection (WoSCC) database, reviewing literature published from January 2019 to December 2023. The analysis involved tools like VOSviewer and R-bibliometrix to visualize networks related to publications, countries, journals, citations, authors, and keywords. Only “article” documents published in English were included.
Key findings from the analysis include:
- A total of 1,811 publications on AI in medicine were identified, released across 565 journals by 12,376 authors affiliated with 3,583 institutions from 97 countries. The field has experienced rapid growth, with a steady rise in publications since 2019, averaging a 28.4% annual increase.
- The United States emerged as the foremost producer of scholarly works, leading in both publication count (709 papers or 39.09%) and total citations (14,764), significantly influencing the field. Strong global collaboration was observed, particularly involving the US, China, England, Germany, and Italy.
- Harvard Medical School demonstrated the highest publication count and level of collaboration among institutions.
- The Journal of Medical Internet Research recorded the highest H-index (19), publication count (76), and total citations (1,495). Other core journals identified include Cancers, BMJ Open, JMIR Medical Informatics, and Journal of Personalized Medicine.
- Analysis of keywords revealed four main clusters for AI applications: digital health, COVID-19 and ChatGPT, precision medicine, and public health epidemiology. Notably, keywords like “Outcomes” and “Risk” have shown a significant upward trend since 2022, pointing to future research directions focusing on patient health condition risks and discussions with clinicians.
In conclusion, this study provides valuable insights into the progress, focus areas, and emerging fields of AI in medicine. It serves as a crucial reference for researchers, medical practitioners, and policymakers, guiding future initiatives toward integrating AI in medicine and optimizing healthcare resource use for enhanced patient quality of life. The findings suggest AI will increasingly play a pivotal role in digital health and public health, significantly improving disease forecasting, identification, diagnosis, categorization, treatment, and survival prediction to foster a sustainable approach for precision medicine.
Reference: Lin, M., Lin, L., Lin, L., Lin, Z., & Yan, X. (2025). A bibliometric analysis of the advance of artificial intelligence in medicine. Frontiers in Medicine, 12, Article 1504428. https://doi.org/10.3389/fmed.2025.1504428