HEALTH CARE CHATBOT USING(LLM)

Large Language Models (LLMs) have progressed very quickly and have therefore improved the capabilities of conversational artificial intelligence systems.In this paper, we have described the design of a Healthcare Chatbot that utilizes a Large Language Model to provide early medical advice through natural language.This chat-based application allows users to provide details of symptoms, ask for specific information about diseases, medications, or preventative care approaches, and receive structured responses in an interactive way.This system uses a transformer-based architecture that allows it to understand context, recognize user intent, and generate coherent responses.The chat application uses prompt engineering methods to ensure that responses are well-structured and consistent, including possible conditions, recommended laboratory tests, precautionary measures, and lifestyle recommendations.The system employs a safety layer to prevent the dissemination of erroneous medical information and encourage users to seek professional healthcare advice when appropriate.This system aims to improve access to healthcare for individuals in hard-to-reach or underserved areas by providing immediate access to health information in an easy-to-use format.Although this system is not intended to replace a trained professional's medical diagnosis, it provides an additional digital support mechanism for providing awareness and early guidance.The results of this study show that there are many opportunities for LLM-based chatbots to help expand digital health services and increase engagement with patients.