A phenotype-driven and evidence-governed framework for knowledge graph enrichment and hypotheses discovery in population data

arXiv:2604.16982v1 Announce Type: new Abstract: Current knowledge graph (KG) construction methods are confirmatory, focusing on recovering known relationships rather than identifying novel or context-dependent nodes. This paper proposes a phenotype-driven and evidence-governed framework that shifts the paradigm toward structured hypothesis discovery and controlled KG expansion. The approach integrates graph neural networks (GNNs) for phenotype discovery, causal inference, probabilistic reasoning