Autores
Tamayo Herrera Antonio Jesús
Gelbukh Alexander
Título mBERT and Simple Post-Processing: A Baseline for Disease Mention Detection in Spanish
Tipo Congreso
Sub-tipo Memoria
Descripción 2022 Conference and Labs of the Evaluation Forum, CLEF 2022
Resumen 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. © 2022 Copyright for this paper by its authors.
Observaciones CEUR Workshop Proceedings, v. 3180
Lugar Bologna
País Italia
No. de páginas 350-356
Vol. / Cap.
Inicio 2022-09-05
Fin 2022-09-08
ISBN/ISSN