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, China

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

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

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

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

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

Corresponding Author:

  • Jun Liao, PhD
  • School of Science
  • China Pharmaceutical University
  • #639 Longmian Avenue
  • Jiangning District
  • Nanjing, 211198
  • China
  • Phone: 86 13952040425
  • Email: liaojun@cpu.edu.cn