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Artificial intelligence application in healthcare management: a review of challenges

Abbas Sorkhi & Faramarz Pourasghar

International Journal of Healthcare Technology and Management2024https://doi.org/10.1504/ijhtm.2024.136547review
AJG 1
Weight
0.48

What the paper says

Integrating computers and machines into tasks traditionally done by humans, artificial intelligence offers significant opportunities for economic growth, social progress, and research. In this paper, we explore the challenges of implementing artificial intelligence in healthcare systems management. Through a scoping review using the Arksey and O'Malley protocol, we searched Medline (via Pubmed), Web of Science, Scopus, and Iranian databases from 1996 to 2022. The implementation and application of artificial intelligence in healthcare management present various challenges. These challenges include data collection, data quality, data accessibility, technology evolution, implementation strategies, cost and return on investment, ethical and social concerns, recruitment, and adoption. Addressing these challenges is crucial and may involve addressing data-related issues, providing accurate and comprehensive data to artificial intelligence systems, developing reliable algorithms, and making informed decisions based on artificial intelligence insights.

4 citations

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https://doi.org/https://doi.org/10.1504/ijhtm.2024.136547

Or copy a formatted citation

@article{abbas2024,
  title        = {{Artificial intelligence application in healthcare management: a review of challenges}},
  author       = {Abbas Sorkhi & Faramarz Pourasghar},
  journal      = {International Journal of Healthcare Technology and Management},
  year         = {2024},
  doi          = {https://doi.org/https://doi.org/10.1504/ijhtm.2024.136547},
}

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Artificial intelligence application in healthcare management: a review of challenges

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Evidence weight

0.48

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.41 × 0.4 = 0.16
M · momentum0.60 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.