Document-level attention-based BiLSTM-CRF incorporating disease dictionary for disease named entity recognition

K Xu, Z Yang, P Kang, Q Wang, W Liu - Computers in biology and medicine, 2019 - Elsevier
Background Disease named entity recognition (NER) plays an important role in biomedical
research. There are a significant number of challenging issues to be addressed; among …

[PDF][PDF] Biomedical named entity recognition based on deep neutral network

L Yao, H Liu, Y Liu, X Li, MW Anwar - Int. J. Hybrid Inf. Technol, 2015 - gvpress.com
Many machine learning methods have been applied on the biomedical named entity
recognition and achieve good results on GENIA corpus. However most of those methods …

[HTML][HTML] Character level and word level embedding with bidirectional LSTM–Dynamic recurrent neural network for biomedical named entity recognition from literature

S Gajendran, D Manjula, V Sugumaran - Journal of Biomedical Informatics, 2020 - Elsevier
Abstract Named Entity Recognition is the process of identifying different entities in a given
context. Biomedical Named Entity Recognition (BNER) is the task of extracting chemical …

基于BERT 的多特征融合农业命名实体识别.

赵鹏飞, 赵春江, 吴华瑞, 王维 - Transactions of the Chinese …, 2022 - search.ebscohost.com
命名实体识别是农业文本信息抽取的重要环节, 针对实体识别过程中局部上下文特征缺失,
字向量表征单一, 罕见实体识别率低等问题, 提出一种融合BERT (Bidirectional Encoder …

A review on conditional random fields as a sequential classifier in machine learning

DY Liliana, C Basaruddin - 2017 International Conference on …, 2017 - ieeexplore.ieee.org
In this paper we present a comprehensive review of a well-known sequential classifier in
machine learning Conditional Random Fields (CRFs). CRFs is proposed to cope the …

Biomedical named entity recognition based on extended recurrent neural networks

L Li, L Jin, Z Jiang, D Song… - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
Biomedical named entity recognition (bio-NER), which extracts important entities such as
genes and proteins, has become one of the most fundamental tasks in biomedical …

Hadoop recognition of biomedical named entity using conditional random fields

K Li, W Ai, Z Tang, F Zhang, L Jiang… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Processing large volumes of data has presented a challenging issue, particularly in data-
redundant systems. As one of the most recognized models, the conditional random fields …

Recognition of the agricultural named entities with multifeature fusion based on albert

P Zhao, W Wang, H Liu, M Han - IEEE Access, 2022 - ieeexplore.ieee.org
High quality agricultural named entity recognition (NER) model can provide effective support
for agricultural information extraction, semantic retrieval and other tasks. However, the …

Recognizing biomedical named entities based on the sentence vector/twin word embeddings conditioned bidirectional LSTM

L Li, L Jin, Y Jiang, D Huang - … Based on Naturally Annotated Big Data …, 2016 - Springer
As a fundamental step in biomedical information extraction tasks, biomedical named entity
recognition remains challenging. In recent years, the neural network has been applied on …

Toward sustainable virtualized healthcare: extracting medical entities from Chinese online health consultations using deep neural networks

H Yang, H Gao - Sustainability, 2018 - mdpi.com
Increasingly popular virtualized healthcare services such as online health consultations
have significantly changed the way in which health information is sought, and can alleviate …