A Software System for Predicting Patient Flow at the Emergency Department of Aalborg University Hospital
Proceedings of the 10th International Conference on Probabilistic Graphical Models, PMLR 138:617-620, 2020.
This paper presents a software system for predicting patient flow at the emergency department of Aalborg University Hospital. The system uses Bayesian networks as the underlying technology for the predictions. A Bayesian network model has been developed for predicting the hourly rate of patients arriving at the emergency department at Aalborg University Hospital. One advantage of using Bayesian networks is that domain knowledge and historical data can easily be combined into an intuitive graphical model. The aim of this paper is to describe the software system delivering the predictions of the Bayesian network model as a decision-support system for employee shift scheduling at the emergency department.