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arXiv AI By Holger R. Roth, Ziyue Xu, Peter Cnudde

FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning

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FedCoRe is a federated learning framework that addresses missing modalities in healthcare by learning representation- or logit-space corrections instead of generating synthetic data. In a MIMIC-derived respiratory deterioration task, the method uses paired examples where a modality is present or absent to train a completion module, achieving partial recovery of performance lost when modalities like ECG or CXR are hidden. The approach emphasizes validation-gated deployment, ensuring that completion is only applied when paired examples and validation evidence support the presence of the missing modality.

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