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Solarte-Pabón OAutor (correspondencia)Blazquez-Herranz AAutor o CoautorRodríguez-González AAutor o CoautorMenasalvas EAutor o Coautor

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Information extraction from Spanish radiology reports using multilingual BERT

Publicado en:Ceur Workshop Proceedings. 2936 834-845 - 2021-01-01 2936(), DOI:

Autores: Solarte-Pabón O; Montenegro O; Blazquez-Herranz A; Saputro H; Rodriguez-González A; Menasalvas E

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This paper describes our team's participation in Task 1 of the Conference and Labs of the Evaluation Forum (CLEF eHealth 2021). The Task 1 challenge targets Named Entity Recognition (NER) from radiology reports written in Spanish. Our approach addresses this challenge as a sequence labeling task and is based on multilingual BERT with a classification layer on top. Three BERT-based models were trained to support overlapping entities extraction: the first model predicts the first specific label annotated in the corpus; the second predicts the second label for tokens that have two different annotations; and the third is used for tokens annotated with a third label in the corpus. Our approach obtained 78.47% and 73.27% for a Lenient and the exact F1 score, respectively. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

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