Who Does Your Algorithm Fail? Investigating Age and Ethnic Bias in the MAMA-MIA Dataset

Documenti analoghi

• Investigating Label Bias and Representational Sources of Age-Related Disparities in Medical Segmentation
  di: Parikh, Aditya, et al.
  Pubblicazione: (2025)
• Fair Lung Disease Diagnosis from Chest CT via Gender-Adversarial Attention Multiple Instance Learning
  di: Parikh, Aditya, et al.
  Pubblicazione: (2026)
• Towards Fairness under Label Bias in Image Segmentation: Impact, Measurement and Mitigation
  di: Parikh, Aditya, et al.
  Pubblicazione: (2026)
• Measuring What VLMs Don't Say: Validation Metrics Hide Clinical Terminology Erasure in Radiology Report Generation
  di: Parikh, Aditya, et al.
  Pubblicazione: (2026)
• Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis using Slice Discovery Methods
  di: Olesen, Vincent, et al.
  Pubblicazione: (2024)