Visualizing chest X-ray dataset biases using GANs

• URL: http://arxiv.org/abs/2305.00147v2
• Date: Tue, 5 Sep 2023 19:12:44 GMT
• Title: Visualizing chest X-ray dataset biases using GANs
• Authors: Hao Liang, Kevin Ni, Guha Balakrishnan
• Abstract summary: Recent work demonstrates that images from various chest X-ray datasets contain visual features that are strongly correlated with protected demographic attributes like race and gender. This finding raises issues of fairness, since some of these factors may be used by downstream algorithms for clinical predictions. In this work, we propose a framework, using generative adversarial networks (GANs), to visualize what features are most different between X-rays belonging to two demographic subgroups.
• Score: 8.61315908717562
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent work demonstrates that images from various chest X-ray datasets contain visual features that are strongly correlated with protected demographic attributes like race and gender. This finding raises issues of fairness, since some of these factors may be used by downstream algorithms for clinical predictions. In this work, we propose a framework, using generative adversarial networks (GANs), to visualize what features are most different between X-rays belonging to two demographic subgroups.

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