August 9, 2025

A Knowledge Graph-Based Intelligent Q&A System for Rare Diseases.

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MAIN FINDING: The intelligent Q&A system effectively enhances access to medical knowledge for rare diseases.
KEY EVIDENCE: The system achieved 82.13% accuracy in entity extraction and 94.54% in intent recognition using advanced models.
APPROACH: Data from 126 rare diseases and 2,609 symptoms were integrated into a knowledge graph for the Q&A system.
SIGNIFICANCE: This system addresses informational gaps in rare diseases, potentially improving diagnosis and treatment.

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A knowledge graph-based Q&A system improves medical knowledge access for rare diseases, indicating potential benefits for patient care.

Chen et al. (2025) studied this question.

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