Imagine an AI system that could diagnose illnesses with the expertise of a seasoned doctor. That's the ambitious goal of KG4Diagnosis, a new framework designed to mimic the hierarchical structure of real-world medical systems. Unlike current AI diagnostic tools, KG4Diagnosis uses a multi-agent approach. Think of it like a digital hospital: a general practitioner AI assesses initial symptoms, then, if needed, refers the case to specialized AI 'consultants' in areas like cardiology or neurology. The secret sauce? A knowledge graph enhanced by cutting-edge Large Language Models (LLMs). This graph acts as a vast medical textbook, constantly updated and validated by human experts. It helps the AI agents understand relationships between symptoms, diseases, and treatments, enabling them to reason more accurately and avoid the 'hallucinations' that plague some AI systems. KG4Diagnosis has been trained on a massive dataset covering hundreds of common diseases. While still under development, early results are promising. This innovative approach could revolutionize healthcare by providing faster, more accurate diagnoses, especially in areas with limited access to specialists. However, challenges remain, including ensuring the system can handle rare diseases and adapting to the ever-evolving landscape of medical knowledge. The future of AI in medicine looks bright, and KG4Diagnosis is leading the way toward a world where AI and human doctors work hand-in-hand to improve patient care.