Abstract
BACKGROUND: Artificial intelligence (AI) has gained widespread attention because of its potential applications in the clinical management of inflammatory bowel disease (IBD). However, bibliometric analyses of the literature published in this field are currently lacking. This study aimed to characterize the development trends and identify research hotspots in the application of AI to IBD through a bibliometric approach. METHODS: Literature related to the application of AI in IBD, published between 2000 and 2024, was retrieved from the Web of Science Core Collection. Microsoft Office Excel 2021 was used to analyze and visualize the annual number of publications. Charticulator was utilized to create country cross chord charts. CiteSpace was employed to visualize collaboration networks among authors, institutions, and countries, generate timeline visualizations and perform a burst analysis of references and keywords. RESULTS: The bibliometric analysis included 1,136 publications published between the years 2000 and 2024. The number of annual publications showed a rapid growth trend. The USA (n = 337) and Harvard University (n = 47) had the most published papers. Stidham, Ryan (n = 21) published the highest number of articles. The core journals shaping the field included Scientific Reports, Inflammatory Bowel Diseases, and PLoS One. The timeline view and burst analysis of references and keywords revealed that the research hotspots focused on radiomics, endoscopy, natural language processing (NLP), and personalized medicine after 2020. CONCLUSION: A growing number of researchers have engaged in exploring the application of AI in IBD, with the USA contributing the most to this field. Currently, the research hotspots mainly involve radiomics, endoscopy, NLP, and personalized medicine. This study provides valuable information for researchers evaluating the application of AI in IBD.