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

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 during training but may be absent at deployment, allowing only those clients to update the completion module. Experiments show that FedCoRe can recover roughly half of the performance lost when ECG or CXR data are hidden, but the framework should only be deployed when paired examples and validation evidence confirm the modality’s presence.

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• multimodal