The global research of artificial intelligence on inflammatory bowel disease: A bibliometric analysis

Aims This study aimed to evaluate the related research on artificial intelligence (AI) in inflammatory bowel disease (IBD) through bibliometrics analysis and identified the research basis, current hotspots, and future development. Methods The related literature was acquired from the Web of Science Core Collection (WoSCC) on 31 December 2024. Co-occurrence and cooperation relationship analysis of (cited) authors, institutions, countries, cited journals, references, and keywords in the literature were carried out through CiteSpace 6.1.R6 software and the Online Analysis platform of Literature Metrology. Meanwhile, relevant knowledge maps were drawn, and keywords clustering analysis was performed. Results According to WoSCC, 1919 authors, 790 research institutions, 184 journals, and 49 countries/regions published 176 AI-related papers in IBD during 1999–2024. The number of papers published has increased significantly since 2019, reaching a maximum by 2023. The United States had the highest number of publications and the closest collaboration with other countries. The clustering analysis showed that the earliest studies focused on “psychometric value” and then moved to “deep learning model,” “intestinal ultrasound,” and “new diagnostic strategies.” Conclusion This study is the first bibliometric analysis to summarize the current status and to visually reveal the development trends and future research hotspots of the application of AI in IBD. The application of AI in IBD is still in its infancy, and the focus of this field will shift to improving the efficiency of diagnosis and treatment through deep learning techniques, big data-based treatment, and prognosis prediction.