Swin Transformer-based intelligent fracture classification and radiographic assessment to support clinical decision-making.

When evaluating the impact of GAN-based data augmentation, the overall accuracy on an independent 10% test set increased from 89.24% to 91.52%, although the McNemar paired test did not reach statistical significance ( p > 0.05).

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