Table 2.
CBAM | FED | GCN | GAN | Cohort | Centre A | Centre B | Centre C | Centre D |
---|---|---|---|---|---|---|---|---|
√ | √ | Train | 0.745 | 0.847 | 0.803 | 0.853 | ||
Test | 0.650 | 0.787 | 0.708 | 0.782 | ||||
√ | √ | √ | Train | 0.719 | 0.783 | 0.862 | 0.941 | |
Test | 0.654 | 0.709 | 0.724 | 0.807 | ||||
√ | √ | √ | Train | 0.751 | 0.778 | 0.805 | 0.802 | |
Test | 0.688 | 0.685 | 0.719 | 0.762 | ||||
√ | √ | √ | √ | Train | 0.750 | 0.814 | 0.811 | 0.875 |
Test | 0.710 | 0.798 | 0.809 | 0.869 |
RFLM robust federated learning model, FED conventional federated learning, GCN graph convolutional neural network, GAN generative adversarial network.