Turkish Journal of Clinics and Laboratory, Год журнала: 2025, Номер 16(1), С. 159 - 166
Опубликована: Март 25, 2025
Aim: This study presents a bibliometric analysis of artificial intelligence (AI)-)-assisted publications in abdominal computed tomography (CT) over the past decade. By examining publication trends, citation patterns, and research collaborations, this offers insights into evolving impact AI imaging. Materials Methods: Data were retrieved from Web Science Core Collection using specific search criteria for 2014–2024. Bibliometric was conducted VOSviewer to generate co-occurrence networks, maps, collaboration patterns. The included keyword analysis, co-authorship co-citation bibliographic coupling. Results: A significant increase AI-related CT has been observed recent years, with deep learning emerging as dominant methodology. Citation network identified key studies focused on image reconstruction, segmentation, radiomics. Collaboration networks highlighted strong international inter-institutional partnerships, particularly among institutions United States, China, South Korea. Additionally, industry-academic notably GE Healthcare, have contributed advancement Conclusions: AI-assisted imaging continues expand critical area research, demonstrating increasing interdisciplinary collaborations. Deep radiomics become focal points, influencing clinical decision support quantitative analysis. Future should prioritize integration routine radiology practice explore its effectiveness through large-scale validation studies.
Язык: Английский