Abstract: Healthcare accessibility remains a major challenge, particularly for elderly individuals, rural populations, and users with limited technical proficiency. Most existing healthcare applications rely on text-based interfaces and complex navigation, which can delay timely medical assistance during critical situations. This paper proposes a Voice-Based Intelligent Healthcare Assistant that enables users to interact with healthcare services through natural voice commands. The system integrates speech recognition, multilingual translation, Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs) to perform symptom analysis and provide contextual health guidance. In addition to symptom assistance, the platform supports voice-driven doctor appointment booking and emergency detection with nearby hospital identification using location-based services. The system is implemented using a React Native mobile interface, FastAPI backend, MongoDB database, and Qdrant vector database for semantic retrieval. Experimental evaluation demonstrates that the proposed system provides accurate symptom interpretation, multilingual accessibility, and real-time responses within a few seconds. The solution improves healthcare accessibility and provides an intuitive digital healthcare support system for diverse populations.

Keywords: Voice-Based Healthcare System, Artificial Intelligence in Healthcare, Retrieval-Augmented Generation, Multilingual Speech Processing, Medical Symptom Analysis, Digital Health Assistant

Downloads: | DOI: 10.17148/IARJSET.2026.13505