Table 1.

Summary of AI algorithms of the included studies

Algorithm Category	Number of studies	percentage
Neural Networks	125	33.3%
Regression	68	18.1%
Tree-Based Models	63	16.8%
Logistic Regression	59	15.7%
Support Vector Machines	41	10.9%
Others	19	5.1%

Neural Networks: CNN, RNN, LSTM, GRU, Transformer, Autoencoder, GAN.

Regression: Linear Regression, Ridge Regression, LASSO, Elastic Net.

Tree-Based Models: Decision Tree, Random Forest, XGBoost, LightGBM, CatBoost, AdaBoost.

Logistic Regression: Binary Logistic Regression, Multinomial Logistic Regression.

Support Vector Machines: Linear SVM, Nonlinear SVM (RBF kernel, Polynomial kernel), SVR.

Others: KNN, Naive Bayes, LDA, Gaussian Processes, K-Means, Hierarchical Clustering, DBSCAN, PCA, t-SNE, UMAP.