Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis.

IF 1.9 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Meng Wang, Yun Peng, Ya Wang, Dehong Luo
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引用次数: 0

Abstract

Background: Radiogenomics is an emerging technology that integrates genomics and medical image-based radiomics, which is considered a promising approach toward achieving precision medicine.

Objective: The aim of this study was to quantitatively analyze the research status, dynamic trends, and evolutionary trajectory in the radiogenomics field using bibliometric methods.

Methods: The relevant literature published up to 2023 was retrieved from the Web of Science Core Collection. Excel was used to analyze the annual publication trend. VOSviewer was used for constructing the keywords co-occurrence network and the collaboration networks among countries and institutions. CiteSpace was used for citation keywords burst analysis and visualizing the references timeline.

Results: A total of 3237 papers were included and exported in plain-text format. The annual number of publications showed an increasing annual trend. China and the United States have published the most papers in this field, with the highest number of citations in the United States and the highest average number per item in the Netherlands. Keywords burst analysis revealed that several keywords, including "big data," "magnetic resonance spectroscopy," "renal cell carcinoma," "stage," and "temozolomide," experienced a citation burst in recent years. The timeline views demonstrated that the references can be categorized into 8 clusters: lower-grade glioma, lung cancer histology, lung adenocarcinoma, breast cancer, radiation-induced lung injury, epidermal growth factor receptor mutation, late radiotherapy toxicity, and artificial intelligence.

Conclusions: The field of radiogenomics is attracting increasing attention from researchers worldwide, with the United States and the Netherlands being the most influential countries. Exploration of artificial intelligence methods based on big data to predict the response of tumors to various treatment methods represents a hot spot research topic in this field at present.

放射基因组学的研究趋势和演变(2005-2023 年):文献计量分析。
背景:放射基因组学是一项新兴技术,它将基因组学与基于医学影像的放射组学相结合,被认为是实现精准医疗的一种前景广阔的方法:本研究旨在利用文献计量学方法定量分析放射基因组学领域的研究现状、动态趋势和发展轨迹:从 Web of Science Core Collection 中检索了截至 2023 年发表的相关文献。使用 Excel 分析年度发表趋势。使用 VOSviewer 构建关键词共现网络以及国家和机构间的合作网络。CiteSpace 用于引文关键词突现分析和可视化参考文献时间轴:共收录了 3237 篇论文,并以纯文本格式导出。论文数量呈逐年上升趋势。中国和美国在该领域发表的论文数量最多,美国的论文被引用次数最高,荷兰的论文平均单篇被引用次数最高。关键词突增分析显示,"大数据"、"磁共振波谱"、"肾细胞癌"、"分期 "和 "替莫唑胺 "等几个关键词近年来出现了引文突增。时间轴视图显示,这些参考文献可分为 8 个集群:低级别胶质瘤、肺癌组织学、肺腺癌、乳腺癌、辐射诱导的肺损伤、表皮生长因子受体突变、晚期放疗毒性和人工智能:放射基因组学领域正吸引着全世界研究人员越来越多的关注,其中美国和荷兰是最有影响力的国家。探索基于大数据的人工智能方法来预测肿瘤对各种治疗方法的反应是目前该领域的研究热点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Interactive Journal of Medical Research
Interactive Journal of Medical Research MEDICINE, RESEARCH & EXPERIMENTAL-
自引率
0.00%
发文量
45
审稿时长
12 weeks
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