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  1. Home
  2. Signal Canvas
  3. MRC-GAT: A Meta-Relational Copula-Based Graph Attention Netw
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MRC-GAT: A Meta-Relational Copula-Based Graph Attention Network for Interpretable Multimodal Alzheimer's Disease Diagnosis

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Viability
0.0/10

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Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 39

Proof: pending

Distribution: unknown

Source paper: MRC-GAT: A Meta-Relational Copula-Based Graph Attention Network for Interpretable Multimodal Alzheimer's Disease Diagnosis

PDF: https://arxiv.org/pdf/2602.15740v1

First buyer signal: unknown

Distribution channel: unknown

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Dimensions overall score 7.0

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Builds On This
MIRAGE: Knowledge Graph-Guided Cross-Cohort MRI Synthesis for Alzheimer's Disease Prediction
Score 6.0down
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3D MRI-Based Alzheimer's Disease Classification Using Multi-Modal 3D CNN with Leakage-Aware Subject-Level Evaluation
Score 5.0down
Builds On This
MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening
Score 6.0down
Prior Work
AD-Reasoning: Multimodal Guideline-Guided Reasoning for Alzheimer's Disease Diagnosis
Score 7.0stable
Prior Work
D-GATNet: Interpretable Temporal Graph Attention Learning for ADHD Identification Using Dynamic Functional Connectivity
Score 7.0stable
Prior Work
Multimodal Connectome Fusion via Cross-Attention for Autism Spectrum Disorder Classification Using Graph Learning
Score 7.0stable
Higher Viability
Tabular LLMs for Interpretable Few-Shot Alzheimer's Disease Prediction with Multimodal Biomedical Data
Score 9.0up
Competing Approach
AD-CARE: A Guideline-grounded, Modality-agnostic LLM Agent for Real-world Alzheimer's Disease Diagnosis with Multi-cohort Assessment, Fairness Analysis, and Reader Study
Score 7.0stable

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