Global research trends and foci of artificial intelligence-based tumor pathology: a scientometric study.

Journal: Journal of translational medicine
Published Date:

Abstract

BACKGROUND: With the development of digital pathology and the renewal of deep learning algorithm, artificial intelligence (AI) is widely applied in tumor pathology. Previous researches have demonstrated that AI-based tumor pathology may help to solve the challenges faced by traditional pathology. This technology has attracted the attention of scholars in many fields and a large amount of articles have been published. This study mainly summarizes the knowledge structure of AI-based tumor pathology through bibliometric analysis, and discusses the potential research trends and foci.

Authors

  • Zefeng Shen
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Jintao Hu
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, 107 Yanjiangxi Road, Yuexiu District, Guangzhou, 510120, Guangdong, China.
  • Haiyang Wu
    Graduate School of Tianjin Medical University, No. 22 Qixiangtai Road, Tianjin, 300070, China.
  • Zeshi Chen
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Weixia Wu
    Zhujiang Hospital, Southern Medical University, 253 Gongye Road M, Guangzhou, 510282, China.
  • Junyi Lin
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Zixin Xu
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
  • Jianqiu Kong
    Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China. kongjq5@mail.sysu.edu.cn.
  • Tianxin Lin
    Departments of Urology, Radiology, Emergency Medicine, and Respiratory Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China. Electronic address: lintx@mail.sysu.edu.cn.