3 papers
q-bio.QM2025
Dual-attention ResNet outperforms transformers in HER2 prediction on DCE-MRI
Naomi Fridman, Anat Goldstein
Breast cancer is the most diagnosed cancer in women, with HER2 status critically guiding treatment decisions. Noninvasive prediction of HER2 status from dynamic contrast-enhanced M…
cs.AI2025
Transformer Classification of Breast Lesions: The BreastDCEDL_AMBL Benchmark Dataset and 0.92 AUC Baseline
Naomi Fridman, Anat Goldstein
Breast magnetic resonance imaging is a critical tool for cancer detection and treatment planning, but its clinical utility is hindered by poor specificity, leading to high false-po…
cs.CV2025
BreastDCEDL: A Comprehensive Breast Cancer DCE-MRI Dataset and Transformer Implementation for Treatment Response Prediction
Naomi Fridman, Bubby Solway, Tomer Fridman +2
Breast cancer remains a leading cause of cancer-related mortality worldwide, making early detection and accurate treatment response monitoring critical priorities. We present Breas…