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New GraphRAG Framework Enhances Clinical Suicide Risk Assessment

By PulseAugur Editorial · [1 sources] ·

Researchers have developed BEACON-SP, a novel framework utilizing an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) approach for clinical suicide risk assessment. This system integrates patient knowledge graphs with ontology-guided retrieval to facilitate multi-hop reasoning across various patient data points, including diagnoses, medications, and life events. Evaluations show that BEACON-SP significantly improves completeness, clinical relevance, and evidence grounding compared to a standard vector-based RAG baseline, with clinicians preferring the GraphRAG approach in most cases. AI

IMPACT This ontology-guided GraphRAG framework could improve clinical decision support by providing structured, contextualized patient evidence for behavioral health settings.

RANK_REASON The cluster describes a new research paper detailing a novel framework for clinical suicide risk assessment. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New GraphRAG Framework Enhances Clinical Suicide Risk Assessment

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The cluster describes a new research paper detailing a novel framework for clinical suicide risk assessment. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Nathaniel D. Bastian ·

    BEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment

    We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavioral health settings such as suicide prevention, where effective assessment requires integrating heterogeneous clinical, behavioral,…

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