Fig. 1
From: Interpretable machine learning models for prolonged Emergency Department wait time prediction
Comparison of false negative rates and false positive rates when different machine learning algorithms utilized for wait-time prediction. Figure 1 depicts various false negative rates (FNRs) and false positive rates (FPRs) for predicting patient wait times using different ML algorithms. Our focus was primarily on the FNR in our attempts to predict patients' wait times. A false negative occurs when ML algorithms misclassify a patient who waits longer than 30 minutes as waiting less than 30 minutes. In Figure 1, the highest FNR was observed when using RF algorithm to predict patient wait times, while the lowest FNR was observed when SVM algorithm was utilized. Abbreviations: FNR, False Negative Rate; CVLR, Cross Validation Logistic Regression; RF, Random Forest; XGBoost, eXtreme Gradient Boosting; ANN, Artificial Neural Network; SVM, Select Vector Machine