Published Paper Details:

This paper presents the implementation of a healthcare chatbot powered by Retrieval-Augmented Generation (RAG), designed to provide accurate, reliable, and multilingual health assistance. The chatbot integrates natural language processing (NLP), image recognition, and speech processing technologies to offer personalized and accessible medical sup-port. It leverages open-access health databases for contextually relevant responses and includes computer vision capabilities for analyzing skin conditions. The system supports multilingual voice interactions, enhancing global accessibility to healthcare information. Our implementation demonstrates significant improvements over traditional rule-based healthcare chatbots, particularly in accuracy, multimodal interactions, and accessibility. Keywords--Healthcare, Chatbot, Retrieval-Augmented Generation, Natural Language Processing, Computer Vision, Multi-lingual Support, Artificial Intelligence.