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Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation. (arXiv:2201.03559v1 [eess.IV])
Jan. 12, 2022, 2:10 a.m. | Srishti Gautam, Marina M.-C. Höhne, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
cs.LG updates on arXiv.org arxiv.org
The recent trend of integrating multi-source Chest X-Ray datasets to improve
automated diagnostics raises concerns that models learn to exploit
source-specific correlations to improve performance by recognizing the source
domain of an image rather than the medical pathology. We hypothesize that this
effect is enforced by and leverages label-imbalance across the source domains,
i.e, prevalence of a disease corresponding to a source. Therefore, in this
work, we perform a thorough study of the effect of label-imbalance in
multi-source training for …
More from arxiv.org / cs.LG updates on arXiv.org
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