Table 3.

Performance comparison for COVID-19 detection using different models. LR means logistic regression; KNN means k-nearest neighbors; RF means random forest; SVM means support vector machine; GLM means generalized linear model, which is demonstrated in Section 3.3.2. ACC, accuracy; SN, sensitivity; SP, specificity; AUC, area under the receiver operating characteristic curve. Feature selection YES means that the features were obtained using the feature selection method proposed in Section 3.3.2 (only 10 features were used). Feature selection NO means that 85 radiomic features were used. The normalization YES means that the features were normalized before classification.

	Feature selection	Normalization	Methods	ACC	SN	SP	AUC
1	YES	YES	LR	0.9240	0.9230	0.9250	0.9260
2	YES	YES	KNN	0.8210	0.8970	0.7050	0.9150
3	YES	YES	RF	0.8570	0.8610	0.8550	0.9390
4	YES	YES	SVM	0.9450	0.9850	0.9091	0.9870
5	YES	YES	GLM	0.9460	0.9670	0.9270	0.9470
6	YES	NO	LR	0.7937	0.8773	0.7055	0.9235
7	YES	NO	KNN	0.7502	0.6924	0.7800	0.7673
8	YES	NO	RF	0.8660	0.8606	0.8727	0.9400
9	YES	NO	SVM	0.4735	0.5500	0.4182	0.5087
10	YES	NO	GLM	0.9280	0.9318	0.9272	0.9295
11	NO	YES	LR	0.9379	0.9251	0.9091	0.9356
12	NO	YES	KNN	0.8213	0.8439	0.6872	0.9056
13	NO	YES	RF	0.8217	0.8924	0.7454	0.9012
14	NO	YES	SVM	0.9458	0.9233	0.9191	0.9440
15	NO	NO	LR	0.4822	0.0000	1.0000	0.6484
16	NO	NO	KNN	0.6426	0.8136	0.4618	0.6683
17	NO	NO	RF	0.8217	0.8924	0.7454	0.9012
18	NO	NO	SVM	0.4545	0.6333	0.2600	0.5541