Disease Diagnosis Using Chatbot
DOI:
https://doi.org/10.69996/jsihs.2025018Keywords:
Natural Language Processing (NLP), Disease Prediction, Chatbot, Autoencoder, Deep LearningAbstract
The rapid advancement in artificial intelligence (AI) and natural language processing (NLP) has significantly transformed the healthcare industry by enabling intelligent disease prediction systems. This paper presents an AI-driven disease prediction model integrated with a chatbot interface, designed to analyze patient symptoms and provide potential disease diagnoses along with dietary recommendations. The proposed system utilizes deep learning-based autoencoder architecture for high-dimensional symptom analysis and classification. The model is trained on a rich dataset comprising 199 medical features across numerous disease classes. Upon receiving user input in natural language, the system extracts relevant symptoms, predicts the disease, and responds interactively through the chatbot. This paper presents an innovative healthcare solution titled "Disease Diagnosis Using Chatbot", which leverages artificial intelligence (AI) and natural language processing (NLP) to facilitate preliminary disease diagnosis through interactive conversations. The proposed chatbot system serves as a userfriendly interface, guiding individuals through a series of symptom-related queries to gather relevant health information. By employing machine learning algorithms and NLP techniques, the chatbot interprets user inputs, analyzes symptom patterns, and offers personalized recommendations or potential diagnoses. The objective is to enhance healthcare accessibility, support early identification of medical conditions, and assist users in making informed decisions about seeking professional medical attention. Experimental evaluations demonstrate the chatbot’s effectiveness in identifying a range of common diseases, highlighting its potential to augment traditional healthcare delivery systems with intelligent, AIpowered tools.
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