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This study conducts a comprehensive bibliometric analysis of artificial intelligence (AI) applications in biomedical engineering, exploring the growth, trends, and impact of this transformative technology from 2010 to 2025. Using data from Scopus, the study examines the evolution of AI research in biomedical engineering, highlighting key trends in publications, leading authors, institutions, and countries. The analysis reveals significant growth in AI research, particularly after 2015, driven by advancements in computational power, the availability of large datasets, and the development of sophisticated algorithms. The findings underscore the global nature of AI research, with significant contributions from the United States, China, and the United Kingdom. Key research areas include medical imaging, wearable devices, and predictive analytics. This study provides valuable insights for researchers, biomedical engineers, and policymakers, highlighting the potential of AI to address contemporary challenges in biomedical engineering and guiding future research directions.

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Revolutionizing Biomedical Engineering: A Bibliometric Analysis of Artificial Intelligence Applications and Trends

  • 章节

  • 发表日期：

    2026年

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  • Anber Abraheem Shlash Mohammad,
  • Suleiman Ibrahim,
  • Asokan Vasudevan,
  • Khaleel Al-Daoud,
  • Nawaf Alshdaifat,
  • Abdullah Ibrahim Mohammad,
  • Wenchang Chen,
  • Rajani Balakrishnan,
  • J. Bamini

摘要

This study conducts a comprehensive bibliometric analysis of artificial intelligence (AI) applications in biomedical engineering, exploring the growth, trends, and impact of this transformative technology from 2010 to 2025. Using data from Scopus, the study examines the evolution of AI research in biomedical engineering, highlighting key trends in publications, leading authors, institutions, and countries. The analysis reveals significant growth in AI research, particularly after 2015, driven by advancements in computational power, the availability of large datasets, and the development of sophisticated algorithms. The findings underscore the global nature of AI research, with significant contributions from the United States, China, and the United Kingdom. Key research areas include medical imaging, wearable devices, and predictive analytics. This study provides valuable insights for researchers, biomedical engineers, and policymakers, highlighting the potential of AI to address contemporary challenges in biomedical engineering and guiding future research directions.