Development and Validation of Models
The outcome of this study was medical disputes, which were considered as disputes arising during medical practices between patients or their immediate relatives and physicians or medical institutions because of differing perceptions of treatment outcomes. To identify the characteristics associated with medical disputes, the significant features identified through multivariate analysis were used as input features for the ML model. We used 6 techniques—LR, DT, RF, SVM, GBDT, and DNN—in this study [Validation of the models was conducted using both internal and external sets. We used 12 metrics to evaluate the prediction performance of the models: mean predicted probability, Brier score, intercept, calibration slope, area under the curve (AUC), discrimination slope, specificity, sensitivity, negative predictive value, precision (positive predictive value), Youden index, and accuracy. The equations used to calculate the Brier score, specificity, sensitivity, negative predictive value, precision, Youden index, and accuracy are presented in 