MediAgent AI: An Agentic AI-Based Healthcare Information Chatbot for Public Health Awareness

Abstract

This paper presents MediAgent AI, a prototype healthcare information chatbot built on an agentic artificial intelligence architecture. Developed on the Botpress conversational AI platform, the system applies natural language processing to interpret user queries spanning symptoms, disease prevention, dietary guidance, and general health topics, drawing exclusively from World Health Organization knowledge repositories to ensure evidence-based responses. Unlike conventional rule-based healthcare chatbots, MediAgent AI employs an agentic design in which the system autonomously navigates query understanding, intent detection, knowledge retrieval, and response synthesis without reliance on fixed decision trees. The chatbot is explicitly scoped as an informational tool: it does not diagnose diseases, prescribe medications, or substitute for professional medical consultation, ensuring full compliance with healthcare AI ethics standards. Empirical evaluation across 200 standardised queries yields an overall weighted accuracy of 87.4%, a mean response latency of 1.8 seconds, and a user satisfaction rating of 4.3 out of 5.0 (n = 20). The paper describes the system architecture, sub-agent design, knowledge integration methodology, and comparative performance analysis, and concludes with a discussion of limitations and prospective research directions. The findings suggest that MediAgent AI represents a cost-effective and scalable complement to public health education initiatives.

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