Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26407, first published .
Chinese-Named Entity Recognition From Adverse Drug Event Records: Radical Embedding-Combined Dynamic Embedding–Based BERT in a Bidirectional Long Short-term Conditional Random Field (Bi-LSTM-CRF) Model

Chinese-Named Entity Recognition From Adverse Drug Event Records: Radical Embedding-Combined Dynamic Embedding–Based BERT in a Bidirectional Long Short-term Conditional Random Field (Bi-LSTM-CRF) Model

Chinese-Named Entity Recognition From Adverse Drug Event Records: Radical Embedding-Combined Dynamic Embedding–Based BERT in a Bidirectional Long Short-term Conditional Random Field (Bi-LSTM-CRF) Model

Hong Wu 1, MS;  Jiatong Ji 2, MS;  Haimei Tian 3, MS;  Yao Chen 1, MS;  Weihong Ge 4, MS;  Haixia Zhang 4, PhD;  Feng Yu 2, PhD;  Jianjun Zou 5, PhD;  Mitsuhiro Nakamura 6, PhD;  Jun Liao 1, PhD

1 School of Science, China Pharmaceutical University , Nanjing , CN

2 School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University , Nanjing , CN

3 School of Computer Engineering, Jinling Institute of Technology , Nanjing , CN

4 Department of Pharmacy, Nanjing Drum Tower Hospital , Nanjing , CN

5 Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing , CN

6 Laboratory of Drug Informatics, Gifu Pharmaceutical University , Gifu , JP

Corresponding Author:

  • Jun Liao, PhD
  • School of Science
  • China Pharmaceutical University
  • #639 Longmian Avenue
  • Jiangning District
  • Nanjing
  • CN
  • Phone: 86 13952040425
  • Email: liaojun@cpu.edu.cn