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SYSTEMATIC REVIEW article

Front. Med.
Sec. Nuclear Medicine
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1501652
This article is part of the Research Topic Recent developments in artificial intelligence and radiomics View all articles

Bibliometric and visual analysis of radiomics for evaluating lymph node status in oncology

Provisionally accepted
Guiwen Lyu Guiwen Lyu 1Tong Tong Tong Tong 2*Gen-Dong Yang Gen-Dong Yang 1*Jing Zhao Jing Zhao 1*Zi-Fan Xu Zi-Fan Xu 3*Na Zheng Na Zheng 3,4Zhi-Fang Zhang Zhi-Fang Zhang 1*
  • 1 Shenzhen Third People’s Hospital, Shenzhen, Guangdong Province, China
  • 2 The Second Clinical Medical College, Jinan University, Shen zhen, China
  • 3 School of Medicine, Shenzhen University, Shenzhen, Guangdong Province, China
  • 4 Shenzhen University, Shenzhen, China

The final, formatted version of the article will be published soon.

    Background: Radiomics, which involves the conversion of digital images into high-dimensional data, has been used in oncological studies since 2012. We analyzed the publications that had been conducted on this subject using bibliometric and visual methods to expound the hotpots and future trends regarding radiomics in evaluating lymph node status in oncology.Methods: Documents published between 2012 and 2023, updated to August 1, 2024, were searched using the Scopus database. VOSviewer, R Package, and Microsoft Excel were used for visualization.Results: A total of 898 original articles and reviews written in English and be related to radiomics for evaluating lymph node status in oncology, published between 2015 and 2023, were retrieved. A significant increase in the number of publications was observed, with an annual growth rate of 100.77%.The publications predominantly originated from three countries, with China leading in the number of publications and citations. Fudan University was the most contributing affiliation, followed by Sun Yatsen University and Southern Medical University, all of which were from China. Tian J. from the Chinese Academy of Sciences contributed the most within 5885 authors. In addition, Frontiers in Oncology had the most publications and transcended other journals in recent four years. Moreover, the keywords cooccurrence suggested that the interplay of "radiomics" and "lymph node metastasis," as well as "major clinical study" were the predominant topics, furthermore, the focused topics shifted from revealing the diagnosis of cancers to exploring the deep learning-based prediction of lymph node metastasis, suggesting the combination of artificial intelligence research would develop in the future.The present bibliometric and visual analysis described an approximately continuous trend of increasing publications related to radiomics in evaluating lymph node status in oncology and revealed that it could serve as an efficient tool for personalized diagnosis and treatment guidance in clinical patients, and combined artificial intelligence should be further considered in the future.

    Keywords: Radiomics, Lymph Node, oncology, artificial intelligence, bibliometric analysis

    Received: 25 Sep 2024; Accepted: 28 Oct 2024.

    Copyright: © 2024 Lyu, Tong, Yang, Zhao, Xu, Zheng and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Tong Tong, The Second Clinical Medical College, Jinan University, Shen zhen, China
    Gen-Dong Yang, Shenzhen Third People’s Hospital, Shenzhen, Guangdong Province, China
    Jing Zhao, Shenzhen Third People’s Hospital, Shenzhen, Guangdong Province, China
    Zi-Fan Xu, School of Medicine, Shenzhen University, Shenzhen, 518060, Guangdong Province, China
    Zhi-Fang Zhang, Shenzhen Third People’s Hospital, Shenzhen, Guangdong Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.