Hierarchical federated edge learning with criticality-aware aggregation for privacy-preserving fetal health classification
A novel Criticality-Aware Federated Learning framework with Hierarchical Edge Aggregation, designated as FedCrit-HEA, which achieves a global macro-averaged F1-score of 0.904 and a pathological-class recall of 84.2% on the UCI partition, and reduces wide-area network communication overhead by up to 75% compared to conv...