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Related Experiment Video

Updated: Jun 13, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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KNowNEt:Guided Health Information Seeking from LLMs via Knowledge Graph Integration.

Youfu Yan, Yu Hou, Yongkang Xiao

    IEEE Transactions on Visualization and Computer Graphics
    |September 10, 2024
    PubMed
    Summary

    KnowNet enhances health information seeking by integrating Large Language Models (LLMs) with Knowledge Graphs (KGs). This system improves accuracy and provides structured exploration for reliable health insights.

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    Area of Science:

    • Health Informatics
    • Artificial Intelligence
    • Data Visualization

    Background:

    • Large Language Models (LLMs) pose risks for health information seeking due to potential misinformation.
    • Complex health topics require accurate and structured information access.

    Purpose of the Study:

    • Introduce KnowNet, a system integrating LLMs and Knowledge Graphs (KGs) for enhanced health information accuracy and exploration.
    • Address the risks associated with LLM-generated health information.

    Main Methods:

    • KnowNet extracts triples from LLM outputs and maps them to validated information in external KGs for accuracy.
    • It offers next-step recommendations based on KG entity neighborhoods for structured exploration.
    • A progressive graph visualization monitors inquiries and links exploration history with recommendations.

    Main Results:

    • Demonstrated effectiveness of KnowNet through use cases and expert interviews.
    • Showcased the system's ability to provide accurate and structured health information.
    • Validated the progressive graph visualization for comprehensive understanding.

    Conclusions:

    • KnowNet offers a robust solution for navigating complex health information using LLMs and KGs.
    • The system enhances reliability and user understanding in health information seeking.
    • Integration of LLMs with KGs via visualization is a promising approach for trustworthy AI in healthcare.