Personalized federated learning for equitable breast cancer detection in underrepresented Pacific Islander populations
Published in 7th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF 2026), Strasbourg, France, 2026
First author. Oral presentation. Directly preliminary to my dissertation work on federated adaptation.
My contribution: I conceived and led this study, adapted GMIC for federated fine-tuning under NVIDIA FLARE, built the three-site federation and its preprocessing pipeline, implemented and ran all shared-global and personalized strategies including the module-wise Ditto variant, analyzed the results, and wrote the manuscript.
Evidence of venue quality: 24 submissions, 14 accepted (58%); 7 of the 14 selected for oral presentation, placing this paper in the top 29% of submissions. 7th edition as a MICCAI satellite event; proceedings published by Springer.
Recommended citation: Sollis LJ, Young PM, Bunnell A, Quon B, Hernandez BY, Wolfgruber TK, Shepherd JA. (2026). "Personalized federated learning for equitable breast cancer detection in underrepresented Pacific Islander populations." 7th MICCAI Workshop on Distributed, Collaborative and Federated Learning (DeCaF), Strasbourg, France.
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