NLP

🎯 Project Overview In Emergency Departments (ED), accurate prediction of resource utilization (like IV fluids) is critical for operational efficiency. Traditional models often ignore the rich information hidden in unstructured patient narratives (Chief Complaints). This project aimed to bridge this gap by developing a Multimodal Machine Learning pipeline that integrates structured clinical variables with NLP-derived text features. 🛠 Methodology Data Source Analyzed 13,115 patient records from the National Hospital Ambulatory Medical Care Survey (NHAMCS-ED). Input: Mixed data types including demographics (structured) and triage notes (unstructured). The “Early Fusion” Strategy I implemented an Early Fusion approach to combine distinct data modalities: ...