|
Performance of the decision stump classifier
|
|
Evaluation method
|
Sensitivity
|
Accuracy
|
Specificity
|
AUC
|
PPVa
|
NPVa
|
|
10-fold cross validation
|
67.2 %
|
73.4 %
|
74.9 %
|
0.710
|
38.1 %
|
91.0 %
|
|
testing on each patient’s last assessment
|
51.1 %
|
73.9 %
|
82.0 %
|
0.665
|
50.0 %
|
82.6 %
|
|
Performance of the six advanced classifiers measured by the 10-fold cross validation method
|
|
Classifier
|
Sensitivity
|
Accuracy
|
Specificity
|
AUC
|
PPVa
|
NPVa
|
|
Multiboost with decision stumps
|
73.8 %
|
71.8 %
|
71.4 %
|
0.761
|
37.1 %
|
92.4 %
|
|
Support vector machine
|
71.5 %
|
72.0 %
|
72.0 %
|
0.718
|
37.0 %
|
91.8 %
|
|
Deep learning
|
71.6 %
|
72.3 %
|
72.5 %
|
0.744
|
37.2 %
|
91.8 %
|
|
Naive Bayes
|
59.8 %
|
78.1 %
|
82.3 %
|
0.777
|
43.7 %
|
90.0 %
|
|
k-nearest neighbor
|
56.9 %
|
73.3 %
|
77.0 %
|
0.704
|
36.0 %
|
88.7 %
|
|
Random forest
|
48.3 %
|
75.8 %
|
82.0 %
|
0.662
|
37.9 %
|
87.5 %
|
|
Performance of the six advanced classifiers measured by the method of testing on each patient’s last assessment
|
|
Classifier
|
Sensitivity
|
Accuracy
|
Specificity
|
AUC
|
PPVa
|
NPVa
|
|
Multiboost with decision stumps
|
74.5 %
|
74.4 %
|
74.4 %
|
0.757
|
50.7 %
|
89.2 %
|
|
Support vector machine
|
70.2 %
|
73.3 %
|
74.4 %
|
0.723
|
49.3 %
|
87.6 %
|
|
Deep learning
|
68.1 %
|
72.2 %
|
73.7 %
|
0.738
|
47.8 %
|
86.7 %
|
|
Naive Bayes
|
44.7 %
|
73.9 %
|
84.2 %
|
0.783
|
50.0 %
|
81.2 %
|
|
k-nearest neighbor
|
48.9 %
|
73.9 %
|
82.7 %
|
0.773
|
50.0 %
|
82.1 %
|
|
Random forest
|
38.3 %
|
75.6 %
|
88.7 %
|
0.678
|
54.5 %
|
80.3 %
|
