AI –DRIVEN PUBLIC HEALTH CHATBOT FOR DISEASE AWARENESS

Abstract

The rapid growth of digital technologies has significantly transformed the healthcare sector, enabling innovative solutions for disease awareness and preventive care. Despite these advancements, a large portion of the population still lacks access to reliable, real-time healthcare information, particularly in rural and underserved regions. Traditional awareness systems rely on static communication channels such as websites, brochures, and campaigns, which often fail to provide personalized and interactive guidance.
This research proposes an AI-driven public health chatbot designed to deliver accurate, real-time, and user-specific health information. The system leverages Natural Language Processing (NLP), machine learning algorithms, and a structured medical knowledge base to understand user queries and generate context-aware responses. Key components of the framework include data preprocessing, feature extraction, intent classification using probabilistic models, and dynamic response generation.The chatbot integrates verified health data sources and continuously updates its knowledge base to ensure reliability and accuracy. It also incorporates feedback mechanisms to improve performance over time. Overall, the proposed chatbot offers a scalable, efficient, and cost-effective solution for improving public health awareness, reducing misinformation, and supporting early disease prevention.