CausalKnowledgeTrace: A Novel Computational Framework for Automated Literature-Based Causal Graph Construction and Evidence-Based Variable Selection in Biomedic... (opens in new tab)

Background: Variable selection for causal inference from observational biomedical data is challenging, as overlooking confounders or conditioning on colliders leads to biased estimates. While vast causal knowledge exists in biomedical literature, manually extracting this information for principled variable selection is impractical at scale. Methods: We developed CausalKnowledgeTrace, a Python-based computational framework with Django web interface that systematically leverages structured caus...