Chaima Elmejgari

The Reproducibility Gap in Mammographic CAD: Quantifying Patient-Level Leakage Effects on CBIS-DDSM

Studies with deep learning models for mammographic breast cancer classification routinely report AUC values exceeding 0.90 on public benchmarks; however, the validity of these results is rarely examined at the protocol level. A pervasive issue is patient-level data leakage, whereby images from the same patient appear i...