Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity

This paper introduces Logic-GNN, a neuro-symbolic framework that leverages Temporal Graph Neural Networks and Graph Kolmogorov Complexity to detect data entry errors in clinical records. It identifies anomalies as "grammatical violations" in a latent logical grammar of medical interactions, achieving an F1-score of 0.94 on a large clinical dataset.