<![CDATA[This study explores the integration of Artificial Intelligence (AI) into healthcare, examining its applications across various domains, including diagnostic imaging, personalized medicine, predictive analytics, and administrative workflows. AI has demonstrated significant potential to enhance the accuracy, efficiency, and accessibility of medical services. For instance, AI-driven diagnostic tools improve cancer detection, while AI in personalized medicine tailors treatments based on genetic data. However, challenges such as ethical concerns, data privacy, and the "black box" nature of AI algorithms pose barriers to its widespread adoption. The study employs a mixed-method approach, including literature reviews, expert interviews, and case studies, to assess AI's impact on healthcare. Results indicate that while AI has achieved notable successes, such as reduced diagnostic errors and improved patient outcomes, the implementation faces obstacles like staff AI literacy and high costs.]]>
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