LLaMA 3.1 extracts visual rating scores from Dutch neuroradiology reports with 87-96% balanced accuracy but only 66-80% on numerical counts, with few-shot prompting raising the latter to 81-92%.
In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 574–580
2 Pith papers cite this work. Polarity classification is still indexing.
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A pipeline generates synthetic Dutch medical dialogues via fine-tuned LLM and evaluates them quantitatively and qualitatively, showing feasibility but gaps in naturalness.
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Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model
LLaMA 3.1 extracts visual rating scores from Dutch neuroradiology reports with 87-96% balanced accuracy but only 66-80% on numerical counts, with few-shot prompting raising the latter to 81-92%.
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Generating High Quality Synthetic Data for Dutch Medical Conversations
A pipeline generates synthetic Dutch medical dialogues via fine-tuned LLM and evaluates them quantitatively and qualitatively, showing feasibility but gaps in naturalness.