activity
20182021
most citedFine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text

14 citations · 37 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2021

Analysis and classification of main risk factors causing stroke in Shanxi Province

Junjie Liu, Yiyang Sun, Jing Ma +6

In China, stroke is the first leading cause of death in recent years. It is a major cause of long-term physical and cognitive impairment, which bring great pressure on the National…

cs.CL2019

Enriching Medcial Terminology Knowledge Bases via Pre-trained Language Model and Graph Convolutional Network

Jiaying Zhang, Zhixing Zhang, Huanhuan Zhang +3

Enriching existing medical terminology knowledge bases (KBs) is an important and never-ending work for clinical research because new terminology alias may be continually added and…

cs.CL2019★ 1 cited

NE-LP: Normalized Entropy and Loss Prediction based Sampling for Active Learning in Chinese Word Segmentation on EHRs

Tingting Cai, Zhiyuan Ma, Hong Zheng +1

Electronic Health Records (EHRs) in hospital information systems contain patients' diagnosis and treatments, so EHRs are essential to clinical data mining. Of all the tasks in the…

cs.CL2019★ 14 cited

Fine-tuning BERT for Joint Entity and Relation Extraction in Chinese Medical Text

Kui Xue, Yangming Zhou, Zhiyuan Ma +3

Entity and relation extraction is the necessary step in structuring medical text. However, the feature extraction ability of the bidirectional long short term memory network in the…

cs.CL2018★ 8 cited

An attention-based Bi-GRU-CapsNet model for hypernymy detection between compound entities

Qi Wang, Chenming Xu, Yangming Zhou +3

Named entities are usually composable and extensible. Typical examples are names of symptoms and diseases in medical areas. To distinguish these entities from general entities, we…

cs.CL2018★ 14 cited

Incorporating Dictionaries into Deep Neural Networks for the Chinese Clinical Named Entity Recognition

Qi Wang, Yuhang Xia, Yangming Zhou +3

Clinical Named Entity Recognition (CNER) aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, wh…