Abstract
Automatic disease mention extraction is a relevant task due to its various applications in the medical field. During the last decade, many related works have been published, which have accelerated the progress of this research area, but most of them have been carried out in English. In this work, we propose a deep-learning baseline for this task in Spanish. We report an approach based on transfer learning using multilingual BERT and a straightforward post-processing to tackle the problem. Our system does not use any external resources and rely only on efficient fine tuning, which makes it a fair baseline (Micro F1 = 0.5456) for disease mention identification in Spanish using transformer-based models.
Original language | English |
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Pages (from-to) | 350-356 |
Number of pages | 7 |
Journal | CEUR Workshop Proceedings |
Volume | 3180 |
State | Published - 2022 |
Event | 2022 Conference and Labs of the Evaluation Forum, CLEF 2022 - Bologna, Italy Duration: 5 Sep 2022 → 8 Sep 2022 |
Keywords
- Disease mention detection
- multilingual BERT
- named entity recognition (NER)