AI-VaxGuide: An Agentic RAG-Based LLM for Vaccination Decisions
Journal:
arXiv
Published Date:
Jul 4, 2025
Abstract
Vaccination plays a vital role in global public health, yet healthcare
professionals often struggle to access immunization guidelines quickly and
efficiently. National protocols and WHO recommendations are typically extensive
and complex, making it difficult to extract precise information, especially
during urgent situations. This project tackles that issue by developing a
multilingual, intelligent question-answering system that transforms static
vaccination guidelines into an interactive and user-friendly knowledge base.
Built on a Retrieval-Augmented Generation (RAG) framework and enhanced with
agent-based reasoning (Agentic RAG), the system provides accurate,
context-sensitive answers to complex medical queries. Evaluation shows that
Agentic RAG outperforms traditional methods, particularly in addressing
multi-step or ambiguous questions. To support clinical use, the system is
integrated into a mobile application designed for real-time, point-of-care
access to essential vaccine information. AI-VaxGuide model is publicly
available on https://huggingface.co/VaxGuide
