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Okwor, Ifeanyi Anthony, Hitch, Geeta, Hakkim, Saira, Akbar, Shabana, Sookhoo, Dave and Kainesie, John (2024) Digital Technologies Impact on Healthcare Delivery: A Systematic Review of Artificial Intelligence (AI) and Machine-Learning (ML) Adoption, Challenges, and Opportunities. AI, 2024 (5). pp. 1918-1941. ISSN 2673-2688

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Abstract

Abstract

Recent significant advances in the healthcare industry due to artificial intelligence (AI) and machine learning (ML) have been shown to revolutionize healthcare delivery by improving efficiency, accuracy, and patient outcomes. However, these technologies can face significant challenges and ethical considerations. This systematic review aimed to gather and synthesize the current knowledge on the impact of AI and ML adoption in healthcare delivery, with its associated challenges and opportunities. This study adhered to the PRISMA guidelines. Articles from 2014 to 2024 were selected from various databases using specific keywords. Eligible studies were included after rigorous screening and quality assessment using checklist tools. Themes were identified through data analysis and thematic analysis. From 4981 articles screened, a data synthesis of nine eligible studies revealed themes, including productivity enhancement, improved patient care through decision support and precision medicine, legal and policy challen

Item Type: Article
Uncontrolled Keywords: artificial intelligence; machine learning; adoption; challenges and opportunities; healthcare delivery
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Depositing User: Saira Hakkim
URI: https://sure.sunderland.ac.uk/id/eprint/18395

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Uncontrolled Keywords
artificial intelligence; machine learning; adoption; challenges and opportunities; healthcare delivery
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Item ID
18395
Identification Number
ISSN
2673-2688

Users with ORCIDS

ORCID for Geeta Hitch
ORCID for Saira Hakkim

Catalogue record

Date Deposited
22 Oct 2024 13:38
Last Modified
26 Nov 2025 09:09

Contributors

Author
Author
Ifeanyi Anthony Okwor
Author
Shabana Akbar
Author
Dave Sookhoo
Author
John Kainesie

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