Table 2.

Comparison of accuracy of each classification and total accuracy for different methods on the COVID-19 recognition task on image basis

Method		UP-ResNet18	P-ResNet18	UP-ResNet50	P-ResNet50	P value${}^{\text{a}}$	P value${}^{\text{b}}$	P value${}^{\text{b}}$
Accuracy, mean (sd) (%)	COVID-19	94.47 (5.09)	97.32 (1.45)	95.69 (2.67)	97.79 (1.14)	0.021	0.021	0.041
	Other pneumonias	96.02 (1.62)	96.15 (1.62)	95.01 (1.20)	96.75 (1.37)	0.031	0.027	0.039
	Normal	94.79 (4.41)	96.75 (1.96)	94.93 (3.26)	97.72 (1.41)	0.024	0.022	0.034
Total accuracy, mean (sd) (%)		92.64 (5.38)	95.48 (1.68)	92.82 (3.08)	96.43 (1.36)	0.026	0.012	0.034

Accuracy: $(N_{x,tp}+N_{x,tn})/(N_{x,tp}+N_{x,tn}+N_{x,fp}+N_{x,fn})$

Total accuracy: ${\sum }_x^3{N}_{x,tp}/N$

${}^{\text{a}}$P values for the comparison of accuracy of UP-ResNet18 vs P-ResNet50

${}^{\text{b}}$P values for the comparison of accuracy of UP-ResNet50 vs P-ResNet50

${}^{\text{c}}$P values for the comparison of accuracy of P-ResNet18 vs P-ResNet50. P < 0.05 indicates a significant difference