DRExplainer: Quantifiable Interpretability in Drug Response Prediction with Directed Graph Convolutional Network

arXiv:2408.12139 · cs.LG, cs.AI · Submitted 2024-08-22 · Read on arXiv

cs.LG, cs.AI

Submitted: 2024-08-22

Updated: 2025-03-28

Code: https://github.com/vshydream/DRExplainer

Terminology

• Interpretability — 34× in this paper · explained in 15 episodes
• Benchmark — 13× in this paper · explained in 2 episodes
• AUC — 11× in this paper · explained in 2 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Adjacency Matrix — 8× in this paper · explained in 1 episode
• Embeddings — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Heterogeneous Graph — 3× in this paper · explained in 2 episodes
• Cancer Cell Line Encyclopedia — 2× in this paper
• Computational Biology — 2× in this paper · explained in 2 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Explainability — 2× in this paper · explained in 3 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Graph Neural Network (GNN) — 2× in this paper · explained in 2 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Activation Function — 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
• Aggregation — 1× in this paper · explained in 1 episode
• Area Under the Receiver Operating Characteristic Curve — 1× in this paper
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• GNNs — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Matrix Completion — 1× in this paper · explained in 3 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Predictive Modeling — 1× in this paper · explained in 2 episodes

Sources

• Semi-Supervised Classification with Graph Convolutional Networks
• ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions
• Embedding Entities and Relations for Learning and Inference in Knowledge Bases
• A Survey of Methods for Managing the Classification and Solution of Data Imbalance Problem

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