A multi-task JEPA-pretrained Vision Transformer achieves 0.949 AUC for cancer triage and 0.953 AUC for binary density classification after training on 71k studies from 14 sites.
A review of the role of augmented intelligence in breast imaging: From automated breast density assessment to risk stratification,
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AEGIS: A Multi-Task Joint-Embedding Predictive Architecture for Mammography
A multi-task JEPA-pretrained Vision Transformer achieves 0.949 AUC for cancer triage and 0.953 AUC for binary density classification after training on 71k studies from 14 sites.