Emergency Department Triage Prediction Model

Emergency department triage prediction models aim to automate the prioritization of patients based on their urgency of need, improving efficiency and patient outcomes. Current research focuses on leveraging large language models (LLMs) and other machine learning techniques, including graph neural networks, to analyze patient data (vital signs, symptoms, medical history) from electronic health records and other sources to predict triage acuity. These models show promise in improving triage accuracy and resource allocation, particularly in high-volume settings and during mass casualty incidents, although challenges remain in data availability, model interpretability, and ensuring equitable performance across diverse patient populations.