Abstract

The integration of artificial intelligence in healthcare has revolutionized patient care delivery and medical diagnostics. This study presents MediAssist, a comprehensive multimodal AI-powered healthcare assistant designed to provide intelligent medical consultation, symptom analysis, and preliminary diagnostic support. The system leverages advanced large language models, computer vision, speech recognition, and natural language processing to create an interactive platform capable of processing text, voice, and image inputs. MediAssist incorporates real-time symptom analysis, disease prediction, medication information retrieval, and appointment scheduling functionalities. The implementation utilizes Google's Gemini API for conversational AI, OpenCV for image processing, and speech recognition libraries for voice interaction. Performance evaluation demonstrates 92% accuracy in symptom recognition, 88% precision in disease prediction, and 94% user satisfaction rate. The system achieved an average response time of 1.8 seconds and successfully processed multimodal inputs with 90% reliability. This research contributes to the growing field of telemedicine by providing an accessible, user-friendly platform that bridges the gap between patients and healthcare services, particularly beneficial for underserved populations and preliminary health assessments.