Federated Semi-Supervised Graph Neural Networks with Prototype-Guided Pseudo-Labeling for Privacy-Preserving Gestational Diabetes Mellitus Prediction

arXiv:2605.01810 · cs.LG, cs.AI · Submitted 2026-05-03 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-05-03

Updated: 2026-09-27

Terminology

• AUROC — 30× in this paper · explained in 2 episodes
• Pseudo-labeling — 16× in this paper · explained in 3 episodes
• Consistency — 14× in this paper · explained in 3 episodes
• Federated Learning — 14× in this paper · explained in 15 episodes
• Embeddings — 13× in this paper · explained in 2 episodes
• Adaptive Graph — 11× in this paper · explained in 1 episode
• Aggregation — 11× in this paper · explained in 1 episode
• Adaptive Graph Refinement — 10× in this paper
• Semi-supervised Learning — 8× in this paper · explained in 4 episodes
• Gestational Diabetes Mellitus — 7× in this paper
• Benchmark — 5× in this paper · explained in 2 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• Pseudo-labels — 4× in this paper · explained in 2 episodes
• Representation Learning — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Graph Convolutional Networks — 3× in this paper
• International Conference on Learning Representations — 3× in this paper
• Ablation study — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Differential Privacy — 2× in this paper · explained in 4 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Federated Learning (FL) — 2× in this paper · explained in 7 episodes
• GNNs — 2× in this paper · explained in 2 episodes
• Graph Construction — 2× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 2× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Data Heterogeneity — 1× in this paper · explained in 3 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Non-IID Data — 1× in this paper · explained in 2 episodes
• Over-smoothing — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Semi-Supervised Learning (SSL) — 1× in this paper · explained in 2 episodes

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