OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis
Updated
Updated · arxiv.org · Sep 9
OmniMed-FL: A Robust Multimodal Federated Learning Framework for Clinical Diagnosis
1 articles · Updated · arxiv.org · Sep 9
Summary
Researchers have introduced OmniMed-FL, a federated learning framework for decentralized clinical diagnosis using both radiographs and synthetic clinical notes.
The system securely combines multimodal data across hospitals without sharing sensitive patient information, outperforming single-modality models in classification tasks.
While promising, the study uses synthetic, class-paired data and further validation with real patient records is needed before clinical deployment.