Clinica l Named Entity Recognition via Bi-directional LSTM-CRF Model

EMR (Electronic Medical Record) refers to the systematized collections of patients’ electronically-stored health information in a digital format. Clinical Named Entity Recognition aims to recognize and extract entity mentions from EMR. In this paper, we introduce a novel neural network architecture based on bidirectional LSTMs and conditional random fields, requiring no massive hand-crafted features or data pre-processing, compared to traditional statistical methods such as HMM and CRF.