Bibliometric analysis on artificial intelligence in gynaecology and obstetrics

Abstract

Abstract Background: Artificial intelligence (AI) has the potential to offer innovative solutions to long-standing problems in gynaecology and obstetrics, such as understanding foetal physiology, improving pregnancy monitoring, and unravelling the molecular complexity of gynaecological cancers. This study comprehensively examines the growing role of AI in this field of medicine and its reflections in scientific literature. Methods: In this study, scientific publications addressing the applications of AI in gynaecology and obstetrics were analysed using bibliometric methods. The articles obtained from the Web of Science database search were examined based on key indicators such as publication numbers, citation trends, collaboration networks, main research areas, and the most influential countries/institutions. Analyses were performed using Vosviewer. Results: A total of 701 articles reviewed and the majority of publications (more than 90%) were published after 2020, respectively, China and the United States were leading the publications. International cooperation was common, with Harvard and Oxford among the institutions mentioned. Most articles were OA, with the National Natural Science Foundation of China (NSFC) as the major funding organization. Based on topics and keywords we can concluded that the authors have focused on deep learning workout, foetal monitoring, and gynaecological cancers. Conclusions: Focusing on critical issues such as foetal monitoring and gynaecological cancers, the global importance of this field is demonstrated by intensive international collaboration led by China and the United States. Keywords: bibliometric analysis; artificial intelligence; gynaecology; obstetrics

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