Research progress in digital pathology: A bibliometric and visual analysis based on Web of Science.

Journal: Pathology, research and practice
PMID: 36274267

Abstract

BACKGROUND: The development of whole slide image and deep neural network technologies has contributed to the paradigm shift in diagnostic pathology and has received much attention from researchers, with related publications increasing yearly and "exploding" in recent years. However, few studies have systematically reviewed "digital pathology" using bibliometric tools. In this study, we will use multiple approaches to visualize and analyze "digital pathology" to provide a comprehensive and objective picture of the field's historical evolution and future development.

Authors

  • Jinjin Zhao
    Key Laboratory of Evidence Science, Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Ministry of Education, Beijing, China; Collaborative Innovation Center of Judicial Civilization, Beijing, China.
  • Zhengqi Han
    China University of Political Science and Law, The Institute for Digital Technology and Law (IDTL), China; The CUPL Scientometrics and Evaluation Center of Rule of Law, China.
  • Yixun Ma
    Key Laboratory of Evidence Science, Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Ministry of Education, Beijing, China; Collaborative Innovation Center of Judicial Civilization, Beijing, China.
  • Hongxia Liu
    College of Food Science and Technology, Key Laboratory of Food Processing and Quality Control, Ministry of Agriculture of China, Nanjing Agricultural University, Nanjing, 210095, People's Republic of China.
  • Tiantong Yang
    Key Laboratory of Evidence Science, Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Ministry of Education, Beijing, China; Collaborative Innovation Center of Judicial Civilization, Beijing, China. Electronic address: ytt_cupl@outlook.com.

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