Abstract
Artificial intelligence (AI) has rapidly emerged as a transformative force in medicine, revolutionizing various aspects of healthcare from diagnostics and treatment to public health and patient care. This narrative review synthesizes evidence from diverse study designs, exploring the current and future applications of AI in medicine. We highlight AI's role in improving diagnostic accuracy, optimizing treatment strategies, and enhancing patient care through personalized interventions and remote monitoring, drawing upon recent advancements and landmark studies. Emerging trends such as explainable AI and federated learning are also examined. While acknowledging the tremendous potential of AI in medicine, the review also addresses the barriers and ethical challenges that need to be overcome, including concerns about algorithmic bias, transparency, over-reliance, and the potential impact on the healthcare workforce. We emphasize the importance of establishing regulatory guidelines, fostering collaboration between clinicians and AI developers, and ensuring ongoing education for healthcare professionals. Despite these challenges, the future of AI in medicine holds immense promise, with the potential to significantly improve patient outcomes, transform healthcare delivery, and address healthcare disparities.