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Scientific mapping of digital twin technology in health: A bibliometric analysis

Author

Listed:
  • Umutcan Altun

    (Hacettepe University / Turkiye)

  • Tuba Aralan

    (Åirnak University / Turkiye)

Abstract

This study aims to understand the current state and potential of digital twin technology in healthcare, and to provide an overview of scientific research in this area. Digital twin technology is an innovative approach that aims to create digital replicas of physical systems, providing real-time data and insights. In this study, 814 articles retrieved from the Web of Science database using pre-defined criteria were analysed using bibliometric analysis methods. The analyses show that the reviewed articles received a total of 17,122 citations, with an average of 21.03 citations per article. In addition, the H-index of the studies was determined to be 57. The articles were mainly published in high-impact journals such as IEEE Access (48 articles) and Sensors (28 articles). Beihang University (22 articles, 2,753 citations) and Nanyang Technological University (11 articles, 124 citations) were identified as the most influential institutions. Among countries, China and the United States emerged as leaders, with strong collaborations in particular with the United Kingdom, Singapore and Canada. The thematic analysis results indicate that digital twin technology in healthcare focuses on key areas such as 'system integration', 'modelling' and 'design'. In particular, concepts such as 'framework', 'health' and 'management' are frequently explored.

Suggested Citation

Handle: RePEc:jle:joujos:jos2628
DOI: 10.47243/jos.2628
as

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