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Found 4 papers, 1 papers with code
Benchmarking bias: Expanding clinical AI model card to incorporate bias reporting of social and non-social factors
Clinical AI model reporting cards should be expanded to incorporate a broad bias reporting of both social and non-social factors.
Image Compression and Decompression Framework Based on Latent Diffusion Model for Breast Mammography
This research presents a novel framework for the compression and decompression of medical images utilizing the Latent Diffusion Model (LDM).
Multivariate Analysis on Performance Gaps of Artificial Intelligence Models in Screening Mammography
However, after controlling for confounding, we found lower FN risk associates with Other race(RR=0. 828;p=. 050), biopsy-proven benign lesions(RR=0. 927;p=. 011), and mass(RR=0. 921;p=. 010) or asymmetry(RR=0. 854;p=. 040); higher FN risk associates with architectural distortion (RR=1. 037;p<. 001).
The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.5M Screening and Diagnostic Mammograms
Developing and validating artificial intelligence models in medical imaging requires datasets that are large, granular, and diverse.
