Author

Shadi Albarqouni

2 papers indexed here

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Open access Aug 2026

When multi-institutional dataset aggregation masks shortcut-like behavior in Foundation Models for medical imaging.

Foundation Models are increasingly used in medical imaging, yet their behavior under severe domain heterogeneity remains poorly understood. We study pretrained image encoders as feature extractors for mammography classification across ten datasets spanning diverse acquisition pipelines, populations, and geographic regi...

E. Germani, Fatima Zeineddine, C. Mourad et al. · Medical Image Analysis · 2 citations · ⚡1

#federated learning Open access Oct 2026

Reducing Clinician Annotation Fatigue in Open-Set Federated Learning: A Client-Adaptive Vision-Language Gatekeeper.

PURPOSE Federated learning enables breast-imaging sites to jointly train mammography artificial intelligence (AI) without sharing images, but radiologists at each site must still annotate selected images during active-learning rounds. We developed and evaluated a client-adaptive vision-language gatekeeper that withhold...

Adea Nesturi, D. Gaviria, Jia-Jun Zeng et al. · Journal of the American Coll... · 0 citations