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. 2022 Jan;77:29–52. doi: 10.1016/j.inffus.2021.07.016

Table 2.

Comparison results of our method vs. state-of-the-art methods performed on the CC-CCII dataset.

Annotation Method Patient Acc. (%) Precision (%) Sensitivity (%) Specificity (%) AUC (%)
Patient-level ResNet-50 [165] 53.44 64.45 63.03 35.71 53.24
COVID-Net [177] 57.13 62.53 84.70 6.16 49.58
COVNet [178] 69.96 70.20 93.33 26.75 81.61
VB-Net [179] 76.11 75.84 92.73 45.38 88.34
Ours 89.97 92.99 91.44 87.25 95.53

Image-level ResNet-50 [165] 52.56 61.60 71.27 18.06 50.19
COVID-Net [177] 60.03 64.81 83.91 15.98 58.39
COVNet [178] 75.55 79.90 83.24 61.37 79.48
Ours 80.41 88.56 80.15 80.89 86.06