The field of medical diagnosis and treatment is undergoing a significant transformation with the integration of artificial intelligence (AI) and large language models (LLMs). Recent developments have focused on creating innovative frameworks that combine dynamic knowledge graphs with LLMs to improve diagnostic accuracy and personalized treatment recommendations. These frameworks have shown promising results in handling complex medical data and providing reliable treatment suggestions. Furthermore, AI-assisted systems are being designed to automate and standardize death investigations, and to drive the entire diagnostic process with minimal physician involvement. Noteworthy papers in this area include: DKG-LLM, which achieves high diagnostic accuracy and treatment recommendation accuracy by integrating a dynamic knowledge graph with a large language model. FEAT, a multi-agent AI system that automates and standardizes death investigations through a domain-adapted large language model. Reverse Physician-AI Relationship, which proposes a paradigm shift in the physician-AI relationship, repositioning AI as the primary director of the diagnostic process.