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#federated learning Preprint Oct 2026

Fed-ADApt: Federated Anytime Depth Adaptation for Resource-Aware Medical Image Segmentation

Federated learning (FL) enables collaborative training of medical image segmentation models without sharing raw patient data, yet existing approaches assume a homogeneous compute budget across institutions, limiting participation of low-resource sites. We propose Fed-ADApt, a depth-adaptive federated framework for UNet...

Abhijeet Parida, Zhi-Fan Jiang, Pooneh Roshanitabrizi et al. · 0 citations
#natural language process... Preprint Oct 2026

Evaluating Biomedical Reranking for LLM-Based Question Answering over Longitudinal Clinical Notes

Patient-specific clinical question answering requires locating the right evidence within long, heterogeneous longitudinal clinical records in which relevant facts may be scattered across encounters, repeated in copied-forward notes, or expressed using different clinical terminology. We evaluated whether biomedical rera...

Maryam Shahbaz Ali, Laura B. Strachan, Caitlin Sherman et al. · 0 citations

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