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Extending artificial intelligence research in the clinical domain: a theoretical perspective

Author

Listed:
  • Renu Sabharwal

    (The University of Newcastle)

  • Shah J. Miah

    (The University of Newcastle)

  • Samuel Fosso Wamba

    (TBS Business School)

Abstract

Academic research to the utilization of artificial intelligence (AI) has been proliferated over the past few years. While AI and its subsets are continuously evolving in the fields of marketing, social media and finance, its application in the daily practice of clinical care is insufficiently explored. In this systematic review, we aim to landscape various application areas of clinical care in terms of the utilization of machine learning to improve patient care. Through designing a specific smart literature review approach, we give a new insight into existing literature identified with AI technologies in the clinical domain. Our review approach focuses on strategies, algorithms, applications, results, qualities, and implications using the Latent Dirichlet Allocation topic modeling. A total of 305 unique articles were reviewed, with 115 articles selected using Latent Dirichlet Allocation topic modeling, meeting our inclusion criteria. The primary result of this approach incorporates a proposition for future research direction, abilities, and influence of AI technologies and displays the areas of disease management in clinics. This research concludes with disease administrative ramifications, limitations, and directions for future research.

Suggested Citation

  • Renu Sabharwal & Shah J. Miah & Samuel Fosso Wamba, 2025. "Extending artificial intelligence research in the clinical domain: a theoretical perspective," Annals of Operations Research, Springer, vol. 348(3), pages 1713-1744, May.
    • Handle: RePEc:spr:annopr:v:348:y:2025:i:3:d:10.1007_s10479-022-05035-1
    DOI: 10.1007/s10479-022-05035-1
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