Computed tomography-based radiomics predicts the fibroblast-related gene EZH2 expression level and survival of hepatocellular carcinoma

Table 6 Results of predicting EZH2 in the training set and validation set based on the logistic and random forest classifier algorithm

Classification model		AUC	Accuracy	Sensitivity	Specificity	F1 score
Validation	Logistic	0.792	0.667	0.800	0.833	0.833
	Random Forest	0.812	0.750	1.000	0.750	0.833
Training	Logistic	0.787	0.750	0.679	0.881	0.744
	Random Forest	1.000	0.938	1.000	1.000	1.000

AUC: Area under the curve.