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No single foundation model rules 3D radiology: across 2.1 million volumetric scans and 108 benchmarks, ConvNets consistently outperform transformers at dense spatial localization, while transformers decisively win on global semantic reasoning.
Tokenizer design can significantly influence the extent of privacy leakage in federated learning, with RadBERT recovering the most clinical terms despite all tokenizers failing to prevent information leakage.
