Research on the developments of artificial intelligence in radiomics for oncology over the past decade: a bibliometric and visualized analysis

过去十年人工智能在肿瘤放射组学领域发展的研究:文献计量学和可视化分析

阅读:2

Abstract

OBJECTIVE: To assess the publications' bibliographic features and look into how the advancement of artificial intelligence (AI) and its subfields in radiomics has affected the growth of oncology. METHODS: The researchers conducted a search in the Web of Science (WoS) for scientific publications in cancer pertaining to AI and radiomics, published in English from 1 January 2015 to 31 December 2024.The research included a scientometric methodology and comprehensive data analysis utilising scientific visualization tools, including the Bibliometrix R software package, VOSviewer, and CiteSpace. Bibliometric techniques utilised were co-authorship, co-citation, co-occurrence, citation burst, and performance Analysis. RESULTS: The final study encompassed 4,127 publications authored by 5,026 individuals and published across 597 journals. China (2087;50.57%) and USA (850;20.6%) were the two most productive countries. The authors with the highest publication counts were Tian Jie (60) and Cuocolo Renato (30). Fudan University (169;4.09%) and Sun Yat-sen University (162;3.93%) were the most active institutions. The foremost journals were Frontiers in Oncology and Cancer. The predominant author keywords were radiomics, artificial intelligence, and oncology research. CONCLUSION: Investigations into the integration of AI with radiomics in oncology remain nascent, with numerous studies concentrating on biology, diagnosis, treatment, and cancer risk evaluation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。