The integration of Artificial Intelligence (AI) technologies is revolutionizing healthcare by driving advancements in disease detection, personalized medicine, and clinical decision support. This chapter provides a comprehensive overview of recent developments in deep learning and machine learning, focusing on generative models for medical data synthesis, deep learning architectures for multimodal data analysis, and advanced techniques for predictive analytics and precision medicine. Key applications discussed include early diagnosis, treatment optimization, and real-time clinical insights, emphasizing the role of AI in addressing challenges such as data scarcity and enhancing diagnostic capabilities. The chapter explores how advanced AI models facilitate the integration of complex and heterogeneous datasets, enabling comprehensive decision-making in healthcare. Furthermore, critical challenges related to data scalability, privacy concerns, model interpretability, and clinical integration are examined. By addressing both opportunities and barriers, this chapter offers valuable insights into the evolving role of AI-driven methodologies in modern healthcare, ultimately aiming to enhance patient outcomes and operational efficiency.