CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness
Deep learning models for medical diagnosis frequently exhibit substantial performance disparities across sensitive subgroups (e.g., race, sex), even when average accuracy is high. While generative data augmentation offers a route to mitigate this, existing strategies are suboptimal; they typically address only one or two dependency channels between sensitive attributes and image features. We formalize the medical image formation process via a structural causal model, revealing that sensitive attributes actually influence image content through four distinct pathways-a structural complexity neglected by prior works. Based on this insight, we introduce CIPHER (Causal Intervention Pathways fo...
| Authors | Xinyu Jia, Weidong Guo, Wangyuan Zhao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 July 2026 |
| Last updated at source | 1 July 2026 |
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