AI-Based First Aid Chatbot Using TF-IDF and Maximum Marginal Relevance for Efficient Symptom-Based Assistance

Abstract: During medical emergencies, having quick access to first aid information is essential, particularly if professional assistance is not readily available. This paper describes a First Aid Chatbot that uses user-reported symptoms to provide basic medical advice. Through a web-based chatbot interface, the system enables users to enter symptoms and provides suitable first aid recommendations that are divided into two categories: immediate remedies and whole-day care recommendations. The chatbot uses methods like Maximum Marginal Relevance (MMR) and deduplication to eliminate repetitive suggestions while processing user inputs and retrieving pertinent responses from a predefined remedy dataset. The system, which is built with Node.js, Express.js, MongoDB, and EJS, attempts to increase accessibility to fundamental medical advice and raise awareness of first aid procedures.

Keywords: First Aid Chatbot, Healthcare Chatbots, Symptom Analysis, Conversational AI,