Reference | Method | Results |
C. Neto et al. [7] | bagging -Decision trees (DT) -Logistic regression (LR) -Random Forest (RF) | RF: 83% Accuracy in predicting complications. Gastric cancer |
K. Kaulanjan et al. [8] | bagging -RF -Support Vector Machine (SVM) -k-Nearest Neighbor (KNN) | RF: 65% Accuracy in predicting recurrence Prostate cancer |
Qun et al. [9] | bagging -DT -RF -SVM | SVM: AUC: 98% for gastric cancer diagnosis |
C. Xu et al. [10] | -RF | AUC: 78.9%, survival prognosis gastric cancer |
L. Fan et al. [12] | -AdaBoost -Linear discriminant analysis -Logistic regression | AdaBoost: AUC: 94% to predict lymphovascular invasion |
W. Leung et al. [13] | -Gradient Boosting (GB) -RL | GB: AUC: 97%, prognosis of gastric cancer occurrence |