The digital transformation and future era: bibliometric view of artificial intelligence application in pediatric surgery - Boshen Shu; Shufeng Zhang; Jian Gao; Lin Wang; Xiaohui Wang (Frontiers in Pediatrics)
IntroductionArtificial intelligence has been extensively used in the personalized diagnosis and treatment of pediatric surgery. Numerous articles have been published related to this research recently. Consequently, we aimed to perform a bibliometric analysis of influential studies to reveal the digital transformation and future era within pediatric surgery.MethodsWe searched publications on artificial intelligence application in pediatric surgery until December 31, 2023, via Web of Science core collection database comprehensively. Of these, the 100 most cited articles were evaluated in detail. Diverse parameters including total citations, publication year, journal, impact factor, impact index, country, organization, keyword, study design and evidence level were analyzed. Bibliometrix package from Rstudio, VOSviewer and GraphPad Prism were used for data analysis and mapping.ResultsA total of 2,799 publications were searched and the 100 most cited articles were published from 1995 to 2023, with a total citation number of 2,770. The top country and organization contributing to this area were the USA and Stanford University, while the Journal of Pediatric Surgery dominated the number of studies from the top 100. Retrospective study and articles with evidence level III were the most common. For keyword co-occurrence analysis, it indicated necrotizing enterocolitis, congenital heart disease and radiomics dominated potential hotspots in the future.ConclusionsThe present study presents a detailed list of the impactful articles on artificial intelligence application in pediatric surgery. It provides insights into potential cooperation and prospects for future research, which plays a helpful reference for researchers studying on artificial intelligence application in pediatric surgery.