Table 12 A comparison of how well MedShieldFL works compared to standard models.

From: MedShieldFL-a privacy-preserving hybrid federated learning framework for intelligent healthcare systems

Model

Precision (%)

Accuracy (%)

Recall (%)

F1-Score (%)

Convergence (Epochs)

C-ResNet

97.65

97.81

97.24

97.49

24

FedAvg

94.32

94.01

93.78

93.89

30

FedHealth

95.76

95.68

95.22

95.44

28

FeTS

96.11

95.91

96.04

95.97

26

MedShieldFL

98.37

98.37

98.38

98.37

22

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