# AI-VaxGuide: An Agentic RAG-Based LLM for Vaccination Decisions

arXiv: https://arxiv.org/abs/2507.03493 · HTML: https://mlsanity.com/paper/2507.03493/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use.
- Builds on 8 of its 28 references that are in the map.
- First posted on arXiv 4 Jul 2025.

## Placed in

- LLM agents and tool use / [Medical and scientific domain agents](https://mlsanity.com/agents/medical-and-scientific-domain-agents/)

## Builds on (most cited first, 8 of 8)

- [Can A Society of Generative Agents Simulate Human Behavior and Inform Public Health Policy? A Case Study on Vaccine Hesitancy](https://mlsanity.com/paper/2503.09639/) (2025)
- [AE-GPT: Using Large Language Models to Extract Adverse Events from Surveillance Reports-A Use Case with Influenza Vaccine Adverse Events](https://mlsanity.com/paper/2309.16150/) (2023)
- [Accuracy of a Large Language Model in Distinguishing Anti- And Pro-vaccination Messages on Social Media: The Case of Human Papillomavirus Vaccination](https://mlsanity.com/paper/2404.06731/) (2024)
- [VaxGuard: A Multi-Generator, Multi-Type, and Multi-Role Dataset for Detecting LLM-Generated Vaccine Misinformation](https://mlsanity.com/paper/2503.09103/) (2025)
- [Optimizing Social Media Annotation of HPV Vaccine Skepticism and Misinformation Using Large Language Models: An Experimental Evaluation of In-Context Learning and Fine-Tuning Stance Detection Across Multiple Models](https://mlsanity.com/paper/2411.14720/) (2024)
- [Large Language Model Chatbot Conversations vs Public Health Materials and Parental HPV Vaccination Intentions: A Randomized Clinical Trial](https://mlsanity.com/paper/2504.20519/) (2025)
- [Decoding Concerns: Multi-label Classification of Vaccine Sentiments in Social Media](https://mlsanity.com/paper/2312.10626/) (2023)
- [Working with Large Language Models to Enhance Messaging Effectiveness for Vaccine Confidence](https://mlsanity.com/paper/2504.09857/) (2025)

## Built on by (most cited first, 1 of 1)

- [Patho-AgenticRAG: Towards Multimodal Agentic Retrieval-Augmented Generation for Pathology VLMs via Reinforcement Learning](https://mlsanity.com/paper/2508.02258/) (2025)

## Abstract (arXiv)

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