activity
20162019
most citedPatientEG Dataset: Bringing Event Graph Model with Temporal Relations to Electronic Medical Records

4 citations · 7 across the 2 of their papers we have counts for

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Showing cs.CLShow all

9 papers · 1 filter

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

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

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.CL2019

CBOWRA: A Representation Learning Approach for Medication Anomaly Detection

Liang Zhao, Zhiyuan Ma, Yangming Zhou +3

Electronic health record is an important source for clinical researches and applications, and errors inevitably occur in the data, which could lead to severe damages to both patien…

cs.CL2019

Question Answering based Clinical Text Structuring Using Pre-trained Language Model

Jiahui Qiu, Yangming Zhou, Zhiyuan Ma +3

Clinical text structuring is a critical and fundamental task for clinical research. Traditional methods such as taskspecific end-to-end models and pipeline models usually suffer fr…

cs.CL2018

Fast and Accurate Recognition of Chinese Clinical Named Entities with Residual Dilated Convolutions

Jiahui Qiu, Qi Wang, Yangming Zhou +2

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…