KG-TRACE fuses genomic features with RotatE KG embeddings via an epistemic trust gate for AMR prediction, reporting 0.976 AUROC on isoniazid resistance in the CRyPTIC cohort plus 92.5% symbolic coverage via a new Biological Grounding Ratio metric.
Constructing knowledge graphs and their biomedical applications
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A phenotype-driven framework integrates GNNs, causal inference, probabilistic reasoning, and LLMs to expand knowledge graphs via multi-objective optimization that balances novelty, relevance, and evidence validation.
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KG-TRACE: A Neuro-Symbolic Framework for Mechanistic Grounding in Antimicrobial Resistance Prediction
KG-TRACE fuses genomic features with RotatE KG embeddings via an epistemic trust gate for AMR prediction, reporting 0.976 AUROC on isoniazid resistance in the CRyPTIC cohort plus 92.5% symbolic coverage via a new Biological Grounding Ratio metric.
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A phenotype-driven and evidence-governed framework for knowledge graph enrichment and hypotheses discovery in population data
A phenotype-driven framework integrates GNNs, causal inference, probabilistic reasoning, and LLMs to expand knowledge graphs via multi-objective optimization that balances novelty, relevance, and evidence validation.