Contributions to Clinical Named Entity Recognition in Portuguese

1 code implementation • WS 2019 • F{\'a}bio Lopes, C{\'e}sar Teixeira, Hugo Gon{\c{c}}alo Oliveira

Having in mind that different languages might present different challenges, this paper presents the following contributions to the area of Information Extraction from clinical text, targeting the Portuguese language: a collection of 281 clinical texts in this language, with manually-annotated named entities; word embeddings trained in a larger collection of similar texts; results of using BiLSTM-CRF neural networks for named entity recognition on the annotated collection, including a comparison of using in-domain or out-of-domain word embeddings in this task.

named-entity-recognition Named Entity Recognition +2