Background: Long treatment times are a major issue in American emergency departments, delaying treatment and straining limited resources like rooms/beds and staff.

Project Objectives:
- Cleaning and feature selection from a large and messy data set
- Build a predictive model of treatment times based on patient health records to determine which factors have the most impact on wait times so future interventions can be tailored to those factors.

Data:
MIMIC-IV, a publicly available hospital data set https://mimic.mit.edu/docs/iv/modules/hosp/