Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies
This study provides empirical evidence to guide the selection of models and pooling strategies for RAG frameworks in healthcare applications. Further studies such as this one are vital for guiding empirically-grounded development of retrieval frameworks, such as in the context of RAG, for the clinical domain.
Authors
- Anoop Mayampurath (ORCID: https://orcid.org/0000-0002-3010-6960)
- Skatje Myers (ORCID: https://orcid.org/0000-0001-9524-8436)
- Timothy A. Miller (ORCID: https://orcid.org/0000-0003-4513-403X)
- 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)
- 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 Colorado Anschutz Medical Campus (US)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1093/jamia/ocae308
- Citations
- 8
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- National Institutes of Health
- U.S. National Library of Medicine