TABLE V. A Comparison With the State-of-the-Art Studies Related to COVID-19 Patients’ Detection. Moreover, S, A, and SP Represent Sensitivity, Specificity, and Accuracy Respectively.

Study	Backbone method	Tasks	Number of cases	Performance	Sharing	Privacy protection
Chen et al. [48]	2D Unet++	COVID-19, viral, baterial and Pneu. classification	106 cases	95.2 %(A)100% (S)93.6%(SP)	No	No
Shi et al. [49]	Random forest	COVID-19, viral/ baterial Pneu. and normal classification	2685 cases	87.9 %(A) 90.7% (S) 83.3%(SP)	No	No
Zheng et al. [50]	2D Unet and 2D CNN	COVID-19, viral, baterial and Pneu. classification	499 Training / 132 Validation	90.7% (S) 91.1%(SP)	No	No
Li et al. [51]	2D-Resnet 50	COVID-19, viral/ baterial Pneu. and normal classification	3920 Training/436 Testing	90.0% (S) 96.0%(SP)	No	No
Jin et al. [52]	2D Unet++ and 2D-CNN	COVID-19, viral, baterial and Pneu. classification	1136 Training / 282 Testing	97.4% (S) 92.2%(SP)	No	No
Song et al [53].	2D-Resnet 50	COVID-19, baterial Pneu. and normal classification	164 Training/ 27 Validation/ 83 Testing	86.0% (A)	No	No
Xu et al. [54]	2D-CNN	Normal, Influenza-A and viral/bacterial Pneu. classification	528 Training / 90 Testing	86.7% (A)	No	No
Jin et al. [55]	2D-CNN	COVID-19, viral, baterial and Pneu. classification	312 Training/ 104 Validation/ 1255 Testing	94.1% (S) 95.5%(SP)	No	No
Wang et al. [56]	2D-CNN	COVID-19 and viral Pneu. classification	250 cases	82.9% (A)	No	No
Wang et al. [6]	3D-ResNet + attention	COVID-19, viral Pneu. and normal classification	3997 5-fold validation / 60 validation/ 600 testing	93.3 %(A) 87.6% (S) 95.5%(SP)	No	No
Ours	Federated Bockchain and Capsule Network	COVID-19, viral Pneu. and normal classification	182 Training/ 45 Testing (patients per hospital)	98.68%(A) 98% (S)	Yes	Yes