Khandaker Ali Ariyan@khandakeraliariyan81159

CortexMed is an AI-powered smart patient triage and hospital queue management platform that improves hospital operations by prioritizing patients based on symptom urgency instead of the traditional first-come, first-served approach. The platform reduces waiting times, improves workflow efficiency, and provides real-time visibility for receptionists, doctors, administrators, and patients. When a patient arrives, the receptionist registers their basic information and symptoms. The symptoms are securely sent to an AI microservice powered by Llama 3.1, which analyzes the case and returns a structured response containing a priority level (P1–P5), an explanation, and a confidence score. The AI is designed as a clinical decision-support tool that assists healthcare professionals with prioritization rather than diagnosing diseases or replacing medical judgment. Based on the AI response, CortexMed dynamically reorganizes the consultation queue, recalculates estimated waiting times, and instantly synchronizes updates across all connected users using Socket.IO. Doctors receive an automatically prioritized queue, receptionists monitor live patient flow, administrators access operational analytics, and patients can track their queue position and estimated waiting time using a unique appointment code without creating an account. The platform is built using Next.js (TypeScript), Express.js, MongoDB, FastAPI, Socket.IO, Tailwind CSS, and Docker, following a scalable microservice architecture. The AI service is independent of the backend, making it easy to upgrade or deploy with AMD GPU acceleration through ROCm for faster inference. By combining AI-assisted triage, intelligent queue optimization, live wait-time prediction, real-time synchronization, and operational analytics, CortexMed transforms traditional hospital queue management into a modern, transparent, and patient-centered healthcare solution that helps hospitals deliver faster and more efficient care.

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