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Explanatory Argument Extraction of Correct Answers in Resident Medical Exams
Comprehensive experimentation with language models for Spanish shows that sometimes multilingual models fare better than monolingual ones, even outperforming models which have been adapted to the medical domain.
EriBERTa: A Bilingual Pre-Trained Language Model for Clinical Natural Language Processing
We demonstrate that EriBERTa outperforms previous Spanish language models in the clinical domain, showcasing its superior capabilities in understanding medical texts and extracting meaningful information.
HiTZ@Antidote: Argumentation-driven Explainable Artificial Intelligence for Digital Medicine
Providing high quality explanations for AI predictions based on machine learning is a challenging and complex task.
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