Related Experiment Video
Updated: Apr 18, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
A bibliometric analysis of the global research landscape on artificial intelligence applications in clinical medicine
Min Li1, Suyu Chen2, Sihan Liu2
1School of First Clinical Medicine/The First Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, China.
Objective:
In the digital era, artificial intelligence (AI) is increasingly used in clinical medicine. To investigate this trend, this study uses bibliometric methods to systematically review the literature on AI applications in clinical medicine from 2010 to 2025, aiming to reveal the global landscape of development.
Methods:
This study employs bibliometric analysis methods based on the Web of Science Core Collection database, utilizing software such as Microsoft Office Excel 2023, Origin, VOSviewer, CiteSpace, and Bibliometrix to analyze the selected literature and identify research trends and hotspots in the application of AI within clinical medicine.
Results:
A total of 2,872 literature articles on AI applications in clinical medicine were included in the analysis. Since 2017, publication volume has increased significantly. Researchers from 114 countries contributed to this field. The United States produced the highest number of articles and led in international collaborations. In total, 1,000 institutions were engaged in AI clinical medicine research, with Harvard Medical School having the highest output (n = 85). 19,537 researchers contributed to the publication of the research report. Arman Rahmim from the University of British Columbia was the most prolific (n = 12), maintaining high productivity between 2020 and 2022. The fields of medicine, general medicine, and internal medicine dominated participation in AI clinical applications. Biomedical sciences showed the highest level of involvement (n = 798). Currently, AI, classification, and prediction studies are at the forefront of AI clinical applications. In 2023, the emergence of ChatGPT, a large language model, brought this technology to the forefront.
Conclusion:
AI fosters rapid growth in global research within clinical medicine. This expansion is driven by technological innovation and spreads across all areas of healthcare. Large language models, such as ChatGPT, have initiated a new growth phase in this field. Their integration with clinical scenarios is accelerating intelligent and convergent advancements.
Related Concept Videos
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Current Trends in Nursing II
Statistical Software for Data Analysis and Clinical Trials
Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Nursing Clinical Information System
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
