This project implements a machine learning-based triage system for emergency rooms, which classifies patients based on their symptoms and vitals using a Random Forest Classifier. The system features real-time patient data integration, a user-friendly GUI built with Tkinter, and secure patient data encryption using Fernet from the cryptography lib

Clinical Decision Support System (CDSS) for Emergency Triage. Python implementation of regional healthcare protocols featuring complex logic, input normalization, and automated clinical pathways

AI-Powered Patient Triage System using Flask and Severity Index Model

Trabalho Faculdade UniFil (Análise e Projeto de Algoritmos) com o seguinte tema: Sistema de Triagem de Pacientes

Emergency department triage system with voice processing, computer vision diagnosis, and intelligent patient-doctor matching. Claude API extracts structured medical data from natural language descriptions. Computer vision analyzes wound photographs for severity assessment. Predictive algorithms optimize resource allocation.