Visual Knowledge Domain of Artificial Intelligence in Computed Tomography: A Review Based on Bibliometric Analysis

Kunshu Zhu, Zefang Shen, Min Wang, Lufang Jiang, Ye Zhang, Tiantong Yang, Haidong Zhang, Mengzhou Zhang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial intelligence (AI)-assisted medical imaging technology is a new research area of great interest that has developed rapidly over the last decade. However, there has been no bibliometric analysis of published studies in this field. The present review focuses on AI-related studies on computed tomography imaging in the Web of Science database and uses CiteSpace and VOSviewer to generate a knowledge map and conduct the basic information analysis, co-word analysis, and co-citation analysis. A total of 7265 documents were included and the number of documents published had an overall upward trend. Scholars from the United States and China have made outstanding achievements, and there is a general lack of extensive cooperation in this field. In recent years, the research areas of great interest and difficulty have been the optimization and upgrading of algorithms, and the application of theoretical models to practical clinical applications. This review will help researchers understand the developments, research areas of great interest, and research frontiers in this field and provide reference and guidance for future studies.

Original languageEnglish
Pages (from-to)652-662
Number of pages11
JournalJournal of Computer Assisted Tomography
Volume48
Issue number4
DOIs
Publication statusPublished - 1 Jul 2024

Keywords

  • artificial intelligence
  • Bibliometrics
  • computed tomography
  • visualization analysis

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