A narrative review on ethical considerations and challenges in AI-driven cardiology.

Introduction: Artificial intelligence (AI) is revolutionizing cardiology by enhancing diagnostic precision, prognostic accuracy, and treatment planning. Its integration raises ethical concerns like bias, privacy, accountability, and the risk of dehumanizing healthcare. This review focuses on navigating these challenges while maximizing AI's potential in patient care. Methodology and aims: A narrative review was conducted to explore the ethical challenges associated with AI in cardiology. Key areas of focus included bias in training datasets, data privacy, the "black-box" nature of AI systems, and the need for transparency and accountability in clinical decision-making. Results and critical insights: AI improves accuracy in diagnosing and managing cardiovascular conditions but presents risks such as exacerbating healthcare disparities and challenges in patient data security. Strategies include creating ethical frameworks, integrating diverse datasets, and emphasizing the importance of clinician-AI collaboration to ensure equitable outcomes. Conclusion and limitations: AI offers transformative opportunities for cardiology, yet its success hinges on addressing ethical, technical, and regulatory challenges. Robust frameworks promoting fairness, transparency, and privacy are crucial. Limitations include a lack of real-world validation and the need for ongoing oversight to adapt to evolving clinical demands.