Muhammad Tanvir Afzal

An ontology-guided knowledge graph and retrieval-augmented LLM framework for interpretable mental health assessment

An ontology-guided framework that integrates a Knowledge Graph, an Ontology-Informed Retrieval Classifier, and a Large Language Model for interpretable mental health detection from social media text demonstrates that the KG–ORC cross-validation gate measurably improves predictive reliability over single component baselines, and that ontology-guided, knowledge-grounded reasoning offers a principled path toward interpretable and knowledge-consistent mental health analysis from social media.