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Extracting TNFi switching reasons and trajectories from real-world data using large language models
0
Zitationen
11
Autoren
2025
Jahr
Abstract
Both GPT-4 and locally deployable LLMs effectively extracted complex treatment trajectories and rationale from clinical notes, supporting their broader utility in scalable EHR review and real-world evidence generation.
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Autoren
Institutionen
- University of California, San Francisco(US)
- Inserm(FR)
- Sorbonne Université(FR)
- Centre d'Immunologie et des Maladies Infectieuses(FR)
- Centre de Recherche Saint-Antoine(FR)
- Immunologie - Immunopathologie - Immunothérapie(FR)
- University of San Francisco(US)
- University of California, Berkeley(US)
- Executive Office of the President(US)