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Found 6 papers, 1 papers with code
Explainable Graph Neural Network for Alzheimer's Disease And Related Dementias Risk Prediction
Employing a GNN approach with claims data enhances ADRD risk prediction and provides insights into the impact of interconnected medical code relationships.
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
Graph representation learning (GRL) has emerged as a pivotal field that has contributed significantly to breakthroughs in various fields, including biomedicine.
Globally Interpretable Graph Learning via Distribution Matching
Graph neural networks (GNNs) have emerged as a powerful model to capture critical graph patterns.
Mining On Alzheimer's Diseases Related Knowledge Graph to Identity Potential AD-related Semantic Triples for Drug Repurposing
The 1, 672, 110 filtered triples were used to train with knowledge graph completion algorithms (i. e., TransE, DistMult, and ComplEx) to predict candidates that might be helpful for AD treatment or prevention.
Knowledge Graph-based Neurodegenerative Diseases and Diet Relationship Discovery
To date, there are no effective treatments for most neurodegenerative diseases.
AutoML using Metadata Language Embeddings
We use these embeddings in a neural architecture to learn the distance between best-performing pipelines.
