Zhang Dewei, Zhu Weiyi, Guo Jun, Chen Wei, Gu Xin
The Department of Neurosurgery, Jing'an District Center Hospital of Shanghai, Fudan University, Shanghai, China.
Front Oncol. 2022 Aug 11;12:978427. doi: 10.3389/fonc.2022.978427. eCollection 2022.
There have been no researches assessing the research trends of the application of artificial intelligence in glioma researches with bibliometric methods.
The aim of the study is to assess the research trends of the application of artificial intelligence in glioma researches with bibliometric analysis.
Documents were retrieved from web of science between 1996 and 2022. The bibliometrix package from Rstudio was applied for data analysis and plotting.
A total of 1081 documents were retrieved from web of science between 1996 and 2022. The annual growth rate was 30.47%. The top 5 most productive countries were the USA, China, Germany, France, and UK. The USA and China have the strongest international cooperative link. Machine learning, deep learning, radiomics, and radiogenomics have been the key words and trend topics. "Neuro-Oncology", "Frontiers in Oncology", and "Cancers" have been the top 3 most relevant journals. The top 3 most relevant institutions were University of Pennsylvania, Capital Medical University, and Fudan University.
With the growth of publications concerning the application of artificial intelligence in glioma researches, bibliometric analysis help researchers to get access to the international academic collaborations and trend topics in the research field.
尚无研究采用文献计量学方法评估人工智能在胶质瘤研究中的应用趋势。
本研究旨在通过文献计量分析评估人工智能在胶质瘤研究中的应用趋势。
检索1996年至2022年期间Web of Science数据库中的文献。使用Rstudio的bibliometrix软件包进行数据分析和绘图。
1996年至2022年期间，从Web of Science数据库共检索到1081篇文献。年增长率为30.47%。发文量排名前5的国家是美国、中国、德国、法国和英国。美国和中国的国际合作联系最为紧密。机器学习、深度学习、放射组学和放射基因组学一直是关键词和热门主题。《神经肿瘤学》《肿瘤学前沿》和《癌症》是排名前3的最相关期刊。排名前3的最相关机构是宾夕法尼亚大学、首都医科大学和复旦大学。
随着人工智能在胶质瘤研究中应用的文献数量不断增加，文献计量分析有助于研究人员了解该研究领域的国际学术合作情况和热门主题。
