“…These results of forecasting accuracy are very close to those in the other studies in the literature, with the variation mainly due to the used dataset and prediction algorithms. The studies were performed using different types of patient data, such as one-year data [4, 5, 9–11, 16, 17], 2- to 6-year data [7, 12–15, 17], 10-year data [19], and the daily number of patient arrivals generally used over a period ranging from 1- to 10-year data (usually 3 years) [8]. Different techniques used for the prediction of patient arrival rate are the ANN [7, 9, 11, 14], the autoregressive integrated moving average (ARIMA) [4, 8, 12–14], the linear regression (LR) [14, 18], the exponential smoothing [14, 15, 18], the logistic regression [5, 10, 11, 19], the decision tree (DT) [1, 10], the gradient boosted machines (GBM) [10], the Poisson regression model [16], the random forest (RF), the AdaBoost (AB), the support vector machine (SVM) [5], and the LSTM model [20].…”