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Responsible Artificial Intelligence as a Secret Ingredient for Digital Health: Bibliometric Analysis, Insights, and Research Directions

Author

Listed:
  • Samuel Fosso Wamba

    (TBS Business School)

  • Maciel M. Queiroz

    (Postgraduate Program in Business Administration
    Mackenzie Presbyterian University)

Abstract

With the unparallel advance of leading-edge technologies like artificial intelligence (AI), the healthcare systems are transforming and shifting for more digital health. In recent years, scientific productions have reached unprecedented levels. However, a holistic view of how AI is being used for digital health remains scarce. Besides, there is a considerable lack of studies on responsible AI and ethical issues that identify and suggest practitioners’ essential insights towards the digital health domain. Therefore, we aim to rely on a bibliometric approach to explore the dynamics of the interplay between AI and digital health approaches, considering the responsible AI and ethical aspects of scientific production over the years. We found four distinct periods in the publication dynamics and the most popular approaches of AI in the healthcare field. Also, we highlighted the main trends and insightful directions for scholars and practitioners. In terms of contributions, this work provides a framework integrating AI technologies approaches and applications while discussing several barriers and benefits of AI-based health. In addition, five insightful propositions emerged as a result of the main findings. Thus, this study’s originality is regarding the new framework and the propositions considering responsible AI and ethical issues on digital health.

Suggested Citation

  • Samuel Fosso Wamba & Maciel M. Queiroz, 2023. "Responsible Artificial Intelligence as a Secret Ingredient for Digital Health: Bibliometric Analysis, Insights, and Research Directions," Information Systems Frontiers, Springer, vol. 25(6), pages 2123-2138, December.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:6:d:10.1007_s10796-021-10142-8
    DOI: 10.1007/s10796-021-10142-8
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