A hierarchical graph network that fuses patient-specific PPI graphs with a clinical patient-similarity graph improves atherosclerosis subtype classification and suggests two molecular clusters per imaging subtype, but the evaluation protocol raises leakage concerns.
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Atherosclerosis through Hierarchical Explainable Neural Network Analysis
A hierarchical graph network that fuses patient-specific PPI graphs with a clinical patient-similarity graph improves atherosclerosis subtype classification and suggests two molecular clusters per imaging subtype, but the evaluation protocol raises leakage concerns.