AI Chatbot for Healthcare: Integrating Natural Language Processing and Predictive Analytics

Abstract

Artificial Intelligence (AI) and Natural Language Processing (NLP) are revolutionizing healthcare by enabling intelligent chatbot systems for disease prediction and health information retrieval. This paper presents an AI-driven chatbot that leverages NLP and Machine Learning (ML) techniques to improve accessibility to medical information and assist users in preliminary disease assessment. The chatbot interacts with users in natural language, analyzing symptom descriptions using NLP techniques such as Named Entity Recognition (NER) and text classification. It employs machine learning models like Decision Trees, Support Vector Machines(SVM),and Deep Learning models such as Recurrent Neural Networks (RNNs) for disease prediction, trained on verified medical datasets. For accurate health information retrieval, the chatbot integrates a medical knowledge base from reputable organizations such as the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC). It also utilizes a hybrid search model combining keyword-based and semantic search techniques. With multi-platform accessibility, including mobile apps and web interfaces, the chatbot ensures broad usability while adhering to security and privacy regulations like HIPAA and GDPR. This AI-powered system has the potential to improve healthcare accessibility, support early disease detection, and reduce unnecessary medical consultations.