Abstract:
NeuraHealth is an AI-driven healthcare system developed to improve patient experience and automate hospital workflows through patient-centric processes. The system addresses a common issue faced by patients who are often unsure about which specialist to consult for their symptoms. Using a custom-trained language model combined with domain-specific medical logic, NeuraHealth identifies symptoms, recommends suitable specialists, suggests precautionary steps, and advises basic diagnostic tests such as blood pressure, cholesterol, and sugar level assessments. A conversational chatbot serves as the primary interaction channel, welcoming pa tients, collecting symptoms, generating structured summaries, and automating appointment bookings. These summaries are forwarded to the doctor’s dashboard to support clinical preparation and decision-making. NeuraHealth also offers a comprehensive web-based plat form that provides dedicated interfaces for doctors, patients, and administrators, enabling streamlined appointment management, record access, and workflow oversight. Additional components include doctor dashboards, an appointment scheduler, and a web-scraping module that continuously enriches the medical knowledge base. Neu raHealth emphasizes iterative refinement, scalability, and adaptability for deployment across multiple hospitals. Unlike conventional solutions, the system adheres to university policies by relying solely on in-house trained models rather than pretrained large language models. Overall, NeuraHealth aims to reduce administrative burden, improve initial patient evaluation, and enhance operational efficiency within healthcare institutions.
