Clinical Name Entity Recognition Based on Recurrent Neural Networks

Abstract

In this paper, we propose a novel approach for clinical name entity recognition based on deep machine learning architecture. The proposed scheme based on two different deep learning architectures: the feed forward networks (FFN), and the recurrent neural network (RNN), allow significant improvement in performance, in terms of different performance measures, including precision, recall and F-score, when evaluated with the CLEF 2016 Challenge task 1 A dataset corresponding to Clinical Nursing Handover. It was possible to achieve an F-score of 66% with RNN architecture, which was higher than most of the other participating systems in the Challenge task.