Label Aware Double Transfer Learning for Cross Specialty Medical Named Entity Recognition

This paper focuses on the problem of entity boundary extraction with different entity lengths, and proposes a deep learning model that combines part-of- speech information

In terms of neural modeling, we introduce a novel neural conditional random field (CRF) for cross-lingual NER that allows for cross-lingual transfer by extracting

We propose an approach for named entity recognition in medical data, using a character-based deep bidirectional recurrent neural network.. Such models can learn features and