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Found 2 papers, 1 papers with code
Debiasing Counterfactuals In the Presence of Spurious Correlations
Deep learning models can perform well in complex medical imaging classification tasks, even when basing their conclusions on spurious correlations (i. e. confounders), should they be prevalent in the training dataset, rather than on the causal image markers of interest.
SwinCheX: Multi-label classification on chest X-ray images with transformers
Our model has been tested with several number of MLP layers for the head setting, each achieves a competitive AUC score on all classes.
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