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The Ethical and Governance Challenges of Artificial Intelligence in Healthcare: A PRISMA 2020 Systematic Review

Simon Peter Mshelmbula, Usman Dahiru Haruna

Abstract

Artificial Intelligence (AI) technologies are increasingly embedded within healthcare systems to support diagnostics, predictive modeling, treatment planning, and clinical decision-making. While these systems offer measurable improvements in efficiency and accuracy, they simultaneously introduce substantial ethical and governance concerns. This systematic review applies the PRISMA 2020 framework to critically synthesize empirical and conceptual literature examining ethical risks associated with AI in healthcare contexts. A structured database search covering publications between 2015 and 2025 was conducted across PubMed, IEEE Xplore, ScienceDirect, and Google Scholar. After duplicate removal, screening, and eligibility assessment, 18 peer- reviewed studies were included in the final qualitative synthesis. The findings reveal four dominant ethical domains: algorithmic bias and fairness concerns, data privacy and governance vulnerabilities, lack of transparency and explainability, and accountability ambiguities. The review further identifies regulatory fragmentation and institutional unpreparedness as systemic barriers to ethical AI deployment. The study concludes that ethical integration of AI in healthcare requires standardized fairness auditing, explainability documentation, multidisciplinary oversight mechanisms, and harmonized regulatory frameworks.

Keywords

Artificial IntelligenceHealthcare EthicsAlgorithmic BiasExplainable AIData GovernancePRISMA 2020Accountability

References

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