EpiKG2DAG: a Framework for Automated DAG Construction from Biomedical Text
EpiKG2DAG is introduced, a framework that supports evidence-anchored candidate DAG generation by transforming unstructured biomedical abstracts into structured epidemiological associations and enables the automated identification of candidate confounders, mediators, and colliders based on graph-theoretic motifs and literature-derived evidence.