Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study
DR.KNOWS offers a robust approach for enhancing diagnostic accuracy and reasoning by integrating structured KG knowledge into LLM-based clinical workflows. Although further work is required to address KG biases and extend generalizability, DR.KNOWS represents progress toward trustworthy artificial intelligence-driven clinical decision support, with a human evaluation framework focused on diagnostic safety and alignment with clinical standards.
Authors
- Brian W. Patterson (ORCID: https://orcid.org/0000-0002-4584-3808)
- Ruizhe Li (ORCID: https://orcid.org/0000-0003-2512-845X)
- Timothy A. Miller (ORCID: https://orcid.org/0000-0003-4513-403X)
- John Caskey (ORCID: https://orcid.org/0000-0001-5665-524X)
- Dmitriy Dligach (ORCID: https://orcid.org/0000-0002-2585-2707)
- Majid Afshar (ORCID: https://orcid.org/0000-0002-6368-4652)
- Matthew M. Churpek (ORCID: https://orcid.org/0000-0002-4030-5250)
- Emma Croxford (ORCID: https://orcid.org/0009-0001-9117-7009)
- Yanjun Gao (ORCID: https://orcid.org/0000-0002-9341-7360)
Institutions
- Boston Children's Hospital (US)
- University of Wisconsin–Madison (US)
- Harvard University (US)
- Loyola University Chicago (US)
- University of Aberdeen (GB)
- University of Colorado Anschutz Medical Campus (US)
Publication Details
- Journal
- JMIR AI
- Published
- 2024-11-07
- DOI
- https://doi.org/10.2196/58670
- Citations
- 42
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 9.82
Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute
- U.S. National Library of Medicine