Analysis of eligibility criteria clusters based on large language models for clinical trial design
Clustering eligibility criteria using LLM embeddings provides a practical and efficient method to summarize critical protocol information. We provide an interactive visualization of the pipeline here.
Authors
- Quentin Haas
- Alban Bornet (ORCID: https://orcid.org/0000-0002-7266-627X)
- Anthony Yazdani (ORCID: https://orcid.org/0000-0003-3309-6128)
- Poorya Amini (ORCID: https://orcid.org/0000-0002-9473-0172)
- Douglas Teodoro (ORCID: https://orcid.org/0000-0001-6238-4503)
- F J van der Meer (ORCID: https://orcid.org/0009-0009-6610-202X)
- Philipp Khlebnikov (ORCID: https://orcid.org/0000-0002-3559-2144)
- Boya Zhang (ORCID: https://orcid.org/0000-0002-4439-8212)
Institutions
- University of Geneva (CH)
- Kulicke & Soffa (Singapore) (SG)
Publication Details
- Journal
- Journal of the American Medical Informatics Association
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1093/jamia/ocae311
- Citations
- 5
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 1.74
Funders
- Innosuisse - Schweizerische Agentur für Innovationsförderung