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.
LLM-DG: Leveraging large language model for enhanced disease prediction via inter-patient and intra-patient modeling
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
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.