Towards Intelligent Healthcare: A Study of AI Applications, Challenges, and Future Trends

Abstract: Artificial Intelligence (AI) is rapidly reshaping modern healthcare systems by enabling intelligent data processing, improving diagnostic precision, and supporting clinical decision-making. With the growth of electronic health records (EHRs), medical imaging, and wearable technologies, healthcare institutions are generating vast amounts of heterogeneous data that require advanced analytical techniques. AI technologies, including machine learning, deep learning, and natural language processing, provide powerful tools to extract meaningful insights from such data. This paper presents a comprehensive and structured review of AI in healthcare, focusing on system architectures, core enabling technologies, real-world applications, and emerging challenges. It highlights recent advancements such as explainable AI, federated learning, and blockchain-integrated healthcare systems. Furthermore, critical concerns related to data privacy, bias, interpretability, and regulatory compliance are examined in detail. The study concludes that while AI significantly enhances healthcare efficiency, accuracy, and accessibility, its successful adoption depends on the development of transparent, ethical, and clinically validated systems.

Keywords: Artificial Intelligence, Healthcare Systems, Deep Learning, Clinical Decision Support, Explainable AI, Smart Healthcare