The study conducted ensemble learning method to improve the model's efficiency by increasing the GH and F1-score. The validation set should be divided according to the stratification principle with a ratio of 80:20 into internal and external validation to ensure generalizability. Three repeats of 10-fold cross-validation were used in internal validation to estimate the model performance.