Using Structured Health Information for Controlled Generation of Clinical Cases in French
Résumé
Text generation opens up new prospects for overcoming the lack of open corpora in fields such as healthcare, where data sharing is bound by confidentiality. In this study, we compare the performance of encoder-decoder and decoder-only language models for the controlled generation of clinical cases in French. To do so, we fine-tuned several pre-trained models on French clinical cases for each architecture and generate clinical cases conditioned by patient demographic information (gender and age) and clinical features.
Our results suggest that encoder-decoder models are easier to control than decoder-only models, but more
Domaines
Informatique [cs]| Origine | Fichiers produits par l'(les) auteur(s) |
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