Name of Disorders

Machine Learning Algorithms

Performance

GAD

RF [108,111]

SVM [110]

99%, 79%

96%

ST

NN [155,156]

RF [157]

RVM [159]

93%, 90%

Recall 0.95

Precision 0.79

72%

PD

Ensemble tree classifier [112]

Bayesian network [115]

SVM [116]

79%

82%

92%

SAD

RF [117]

CNN [118]

89%

87%

PTSD

SVM [119,126,127]

GLL [120]

VC [120]

DBN [124]

XGBoost [125]

82%, AUC = 0.78, 82%

AUC = 0.88

AUC = 0.85

75%

AUC = 0.85

Pediatric

SVM [132,137]

ADTree [133]

J48 [133,146]

RF [135,146]

RL [144]

80%, AUC = 0.83

95%

97%, AUC = 0.97

92%, AUC = 0.97

81%