Table 4.

Comparison of AUC and ACC Between RF and Other Machine Learning Models

Classifiers	AUC	P value	Accuracy	P value
RF	0.802	/	0.784	/
XGBoost	0.777	<0.001	0.716	<0.001
DT	0.738	<0.001	0.745	<0.001
kNN	0.741	<0.001	0.733	<0.001
SVM	0.787	0.010	0.691	<0.001
FCN	0.791	0.034	0.774	0.019

Abbreviations: AUC, area under curve; DT, decision tree; FCN, fully convolutional networks; kNN, k-nearest neighbor; RF, random forest; SVM, support vector machine.