Imagine sifting through mountains of medical research to find the exact information you need to treat a complex disease like Alzheimer's. It's a daunting task, even for experienced medical professionals. Now, a groundbreaking AI tool called AlzheimerRAG is poised to revolutionize how we approach Alzheimer's research by providing fast, accurate, and comprehensive insights from vast amounts of biomedical data. This isn't just about text; AlzheimerRAG integrates image data from research papers, creating a multimodal understanding that goes beyond traditional text analysis. This innovative pipeline leverages the power of large language models (LLMs) like Llama 2 and cutting-edge techniques like retrieval augmented generation (RAG) and knowledge distillation. The result? A more efficient and accurate way to synthesize information, leading to better diagnosis, treatment, and overall understanding of Alzheimer’s. Preliminary experiments show AlzheimerRAG delivers a higher level of clinical relevance compared to traditional methods, extracting actionable knowledge from research papers and even images. The researchers conducted a case study simulating real clinical scenarios, from early diagnosis to caregiver support. In these scenarios, AlzheimerRAG performed remarkably well, demonstrating accuracy comparable to human experts. While further development is ongoing, this multimodal approach promises to transform how medical professionals tackle complex diseases, ultimately helping patients and their families navigate the challenges of Alzheimer's.