A benchmark of text embedding models for semantic harmonization of Alzheimer's disease cohorts
Our findings highlight the importance of domain-specific benchmarks for clinical data harmonization in the field of Alzheimer's disease and motivate standards for naming conventions that may support semi-automated mapping applications in the future.
Authors
- Marc Jacobs (ORCID: https://orcid.org/0000-0003-4153-3930)
- Tim Adams (ORCID: https://orcid.org/0000-0002-2823-0102)
- Holger Fröhlich (ORCID: https://orcid.org/0000-0002-5328-1243)
- Yasamin Salimi (ORCID: https://orcid.org/0000-0002-7773-7786)
- Mehmet Can Ay (ORCID: https://orcid.org/0000-0002-2977-7695)
- Diego Valderrama (ORCID: https://orcid.org/0000-0002-3450-0359)
Institutions
- Fraunhofer Institute for Algorithms and Scientific Computing (DE)
Publication Details
- Journal
- The Journal of Prevention of Alzheimer s Disease
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1016/j.tjpad.2025.100420
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00