DISEASE DIAGNOSIS USING CHATBOT

Abstract

The rapid advancement of artificial intelligence in healthcare has enabled the development of intelligent systems that assist in early disease detection and patient guidance. This paper presents a Disease Diagnosis using Chatbot system, an AI-driven conversational platform designed to provide preliminary medical assistance based on user-reported symptoms. The proposed system employs natural language processing (NLP) techniques to interact with users in a conversational manner, effectively collecting symptom data and mapping it to potential diseases using a trained machine learning model. A Convolutional Neural Network (CNN) is utilized to analyze symptom patterns and predict possible health conditions with improved accuracy. The chatbot integrates a comprehensive disease-symptom database and provides personalized recommendations, including dietary suggestions, home remedies, and relevant medical consultation guidance. Additionally, the system incorporates features such as emergency symptom detection, user registration, and automated email notifications for delivering diagnostic insights. Compared to traditional symptom-checking systems, the proposed approach enhances user engagement, accessibility, and decision-making support through its interactive design. Furthermore, the system emphasizes data privacy and ethical considerations while ensuring a user-friendly experience. The results demonstrate that the chatbot can serve as an effective preliminary diagnostic tool, reducing dependency on manual consultation for minor conditions and promoting timely medical intervention for critical cases. This work highlights the potential of AI-powered chatbots in transforming digital healthcare by providing scalable, accessible, and intelligent diagnostic support systems.