Fig. 1

Schematic representation of the study. Study design and machine learning process. The experimental design included data collection, data preprocessing, data splitting, model development, model validation and performance evaluation. Various modeling techniques have been utilized, including decision tree classification (DTC), random forest classification (RFC), support vector classification (SVC), logistic regression (LR), gradient boosting classification (GBC), and artificial neural network (ANN) methods