Paper

Algorithms

Result

Dataset

Proposed Model Result

[4]

Random forest, Logistic regression, SVM

Accuracy (80.75%, 80.88%, 82%)

IBM Waston

AUC for SVM AUC (87%)

[21]

Naive Bayes

AUC (83%)

IBM Waston

AUC for Naive Bayes same (83%)

[22]

Decision trees, Logistic regression, Neural networks and SVM

Accuracy (62.98, 61.65, 61.40 and 61.78)

Cell2cell

ACC for decision trees (98%) and SVM (99%)

[23]

GP-AdaBoost

AUC (0.91)

Cell2cell

The best AUC for SVM (99%) AdaBoost not used

[24]

C4.5 decision tree

AUC (63.04)

Cell2cell

AUC decision trees (98%)

[25]

SVM

AUC (94.13)

Cell2cell

AUC for SVM (99%)