Decoupling Disease, Covariates, and Individual Variability: A Unified Disentanglement Framework for Medical Image Classification

arXiv:2609.25650 · cs.CV · Submitted 2026-09-22 · Read on arXiv

cs.CV

Submitted: 2026-09-22

Updated: 2026-09-22

Terminology

• Accuracy — 27× in this paper · explained in 1 episode
• AUC — 15× in this paper · explained in 2 episodes
• Transformer — 11× in this paper · explained in 2 episodes
• Contrastive Learning — 10× in this paper · explained in 5 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Representation Learning — 7× in this paper · explained in 2 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Decoupling — 6× in this paper · explained in 2 episodes
• Latent Space — 6× in this paper · explained in 7 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• Latent Representation — 5× in this paper · explained in 2 episodes
• Entanglement — 4× in this paper · explained in 4 episodes
• Self-Supervised Learning — 4× in this paper · explained in 8 episodes
• Activation Function — 3× in this paper · explained in 1 episode
• GNNs — 3× in this paper · explained in 2 episodes
• Generalizability — 3× in this paper · explained in 6 episodes
• Adjacency Matrix — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Graph Isomorphism Network — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Adaptive Graph — 1× in this paper · explained in 1 episode
• Adaptive Mechanism — 1× in this paper · explained in 1 episode
• Adversarial Learning Framework — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Attention Deficit Hyperactive Disorder — 1× in this paper
• Benchmarking — 1× in this paper · explained in 4 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• FMRIB Software Library — 1× in this paper
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Graph Convolutional Network — 1× in this paper
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Residualization — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning (SSL) — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Dual Graph Attention based Disentanglement Multiple Instance Learning for Brain Age Estimation
• Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

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