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AI Based Virtual Patient Assistant Chatbot
(NHCE, 2024) Abhay G 1NH21CS003 Abishek J1NH21CS004 Bharath J1NH21IS037 BHARATWAJ 1NH21IS080
This work introduces an Al-based virtual patient assistant chatbot powered by the LLaMA (Large Language Model Meta Al) architecture, designed to enhance healthcare services by offering efficient, real-time medical assistance. The growing demand for Al-driven healthcare solutions highlights the need for tools that can offer timely, accurate responses with minimal computational overhead. LLAMA, developed by Meta Al, addresses this requirement by providing a highly scalable, low-latency solution, making it ideal for use in medical diagnostics, especially where speed and accuracy are paramount. The virtual assistant engages users through natural language conversations, collecting essential patient information such as name, age, and medical history. This personalized data allows the chatbot to provide tailored responses. The system processes symptoms provided by users in real-time, cross-referencing them with a comprehensive medical database to generate potential diagnoses and treatment recommendations. The use of LLaMA's fine-tuned capabilities ensures that the chatbot offers contextually relevant and medically accurate suggestions, making it a reliable tool for symptom analysis and healthcare advice.