Table 4 Best-performing AI models in included studies
AI Model | Number of Studies as Best Performer | Studies |
|---|---|---|
Support Vector Machine (SVM) | 9 | Zhang et al. (2021a), Booth et al. (2022), Chen et al. (2022), Yang et al. (2022), Raschella et al. (2023), Beheshti and Ko (2024), Jia et al. (2024), Rechichi et al. (2024), Shu et al. (2024) |
Random Forest (RF) | 5 | Bisgin et al. (2020), Byeon (2020), Chong-Wen et al. (2022), Jeon et al. (2022), Shibata et al. (2022) |
LEAPD | 2 | Espinoza et al. (2022), Anjum et al. (2024) |
Artificial Neural Network (ANN) | 1 | Sorensen et al. (2011) |
Correlation-based Feature Subset selection Naïve Bayes (CFS-NB) | 1 | Morales et al. (2013) |
Extra Trees Classifier with ANOVA | 1 | Hosseinzadeh et al. (2023) |
Modified Cole-Kripke Algorithm | 1 | Ko et al. (2022) |
XGBoost | 1 | Chen et al. (2023) |
VMD-Based Convolutional Neural Network (VMD-CNN) | 1 | Parajuli et al. (2023) |
Logistic Regression | 1 | Jian et al. (2024) |
Conditional Inference Forest | 1 | Harvey et al. (2022) |
