Natural Language Processing in Improving Information Retrieval and Knowledge Discovery in Healthcare Conversational Agents

Abstract

Healthcare conversational agents have emerged as valuable tools for assisting users in accessing relevant healthcare information, answering queries, and offering personalized recommendations. This study explores the role of Natural Language Processing (NLP) in improving information retrieval and knowledge discovery within such conversational agents. By leveraging NLP techniques, these agents can comprehend user intent, recognize and link important entities, extract structured information from unstructured data sources, understand natural language nuances, provide accurate question answering, represent medical knowledge, generate contextually appropriate responses, and analyze user sentiment. The study emphasizes the significance of intent recognition in accurately identifying user information needs and retrieving pertinent information. Furthermore, entity recognition and linking facilitate precise information retrieval by associating entities with relevant knowledge bases. Information extraction enables the agents to summarize relevant information and provide evidence-based answers. Natural language understanding empowers agents to handle complex user queries and deliver personalized recommendations. Question answering models based on deep learning techniques ensure accurate responses based on the latest medical research. Knowledge representation through NLP techniques enables comprehensive navigation of complex healthcare knowledge bases. Additionally, language generation facilitates the generation of human-like responses tailored to user needs. Lastly, sentiment analysis assists in understanding user emotions and offering appropriate support. This research demonstrates how the integration of NLP within healthcare conversational agents significantly enhances information retrieval and knowledge discovery, contributing to more effective and personalized healthcare experiences for patients, caregivers, and healthcare professionals.