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Major advancements in domains like diagnosis and personalised treatment will be seen because of the rapid growth of artificial intelligence (AI) in healthcare. But this shift additionally presents significant ethical concerns that need to be carefully considered at every stage of AI's research, use, and impact on society in medical settings. This review summarises the findings of multiple systematic and scoping reviews, as well as studies of specific AI applications published between 2013 and 2025. Additionally, it examines ethical norms from different countries and international organisations objectively. Consistent ethical challenges identified include the "black box" problem (lack of transparency and explainability), algorithmic bias leading to fairness and justice issues, impacts on patient autonomy and informed consent, ambiguities in accountability and responsibility, and critical concerns regarding data privacy and security. Although human-centricity and fairness are common ideals throughout global ethical norms, their regulatory methodologies differ; there are still gaps in worldwide harmonisation and enforcement. Finally, while AI has tremendous potential to improve healthcare, its appropriate and equitable application requires proactive attention to these complex ethical dimensions. There is a substantial gap between high-level ethical ideas and their practical execution. Effective AI in healthcare requires ethical design, strong regulatory frameworks, and ongoing interdisciplinary collaboration.

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