Artificial Intelligence (AI) is increasingly reshaping clinical decision-making in healthcare by enhancing diagnostic precision, improving treatment strategies, and boosting overall efficiency. Tools powered by AI, such as machine learning and predictive models, assist healthcare professionals in interpreting complex data and providing more individualized patient care. Despite these advantages, the adoption of AI brings significant ethical concerns. The use of large volumes of sensitive patient data raises issues related to privacy and data protection. Bias within algorithms may result in unequal treatment outcomes, especially for marginalized groups. Furthermore, unclear lines of accountability make it difficult to determine responsibility when AI influences clinical decisions or contributes to errors. To ensure the responsible use of AI in healthcare, it is crucial to implement strong regulations, maintain transparency, and uphold ethical standards.

Artificial Intelligence, Clinical Decision-Making, Machine Learning, Healthcare Ethics, Algorithmic Bias, Patient Privacy, Medical Diagnostics, Regulatory Frameworks, Precision Medicine, Health Informatics

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