EDAFlow (Emergency Department AI Assisted Flow).
The goal is to develop, validate and deploy and study machine learning algorithms to improve the flow of patients through the Emergency Department (ED). To this end we have constructed a data set of roughly 750,000 ED visits with hardware for data analysis that includes data covering the time from arrival in the ED to departure from the hospital.
We aim to develop tools that will predict end-points such as the need for admission, acute care, imaging, blood tests and others. Tools that are successfully validated will become part of clinical decision support tools that we will evaluate in our ED.
The project is funded by CIHR/NSERC/SSHRC and some funding may available to support students or researchers.
Interested? Send an email to firstname.lastname@example.org