Multi-step forecasting of waiting time on emergency department overcrowding using multilayer perceptron neural network algorithm

A multilayer perceptron artificial neural network (MLP-ANN) was implemented to perform a seven days multi-step prediction of waiting times in the emergency department of a public hospital. A dataset of more than two years was used to training the MLP-ANN. The imputation technique was used to interpolate the data. The dataset was distributed in training and testing with 80 and 20%, respectively. The results of the MLP-ANN were compared with the Persistence and ARIMA models, obtaining much better results than the other two methods, especially on weekends.