Cargando…

Attention-based deep residual learning network for entity relation extraction in Chinese EMRs

BACKGROUND: Electronic medical records (EMRs) contain a variety of valuable medical concepts and relations. The ability to recognize relations between medical concepts described in EMRs enables the automatic processing of clinical texts, resulting in an improved quality of health-related data analys...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zhang, Zhichang, Zhou, Tong, Zhang, Yu, Pang, Yali
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2019
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6454667/ https://www.ncbi.nlm.nih.gov/pubmed/30961580 http://dx.doi.org/10.1186/s12911-019-0769-0

Ejemplares similares

A hybrid method based on semi-supervised learning for relation extraction in Chinese EMRs
por: Yang, Chunming, et al.
Publicado: (2022)

Multi-Level Representation Learning for Chinese Medical Entity Recognition: Model Development and Validation
por: Zhang, Zhichang, et al.
Publicado: (2020)

Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning
por: Feng, Yuntian, et al.
Publicado: (2017)

Relation extraction: advancements through deep learning and entity-related features
por: Zhao, Youwen, et al.
Publicado: (2023)

An attention-based deep learning model for clinical named entity recognition of Chinese electronic medical records
por: Li, Luqi, et al.
Publicado: (2019)

Chinese medical entity recognition based on the dual-branch TENER model
por: Peng, Hui, et al.
Publicado: (2023)

A novel deep learning approach to extract Chinese clinical entities for lung cancer screening and staging
por: Zhang, Huanyao, et al.
Publicado: (2021)

Lexicon and attention-based named entity recognition for kiwifruit diseases and pests: A Deep learning approach
por: Zhang, Lilin, et al.
Publicado: (2022)

A hybrid attention and dilated convolution framework for entity and relation extraction and mining
por: Shan, Yuxiang, et al.
Publicado: (2023)

Medical Named Entity Extraction from Chinese Resident Admit Notes Using Character and Word Attention-Enhanced Neural Network
por: Gao, Yan, et al.
Publicado: (2020)

Protonation of a Glutamate Residue Modulates the Dynamics of the Drug Transporter EmrE
por: Gayen, Anindita, et al.
Publicado: (2016)

Construction and Application of Text Entity Relation Joint Extraction Model Based on Multi-Head Attention Neural Network
por: Xue, Yafei, et al.
Publicado: (2022)

A deep learning model incorporating part of speech and self-matching attention for named entity recognition of Chinese electronic medical records
por: Cai, Xiaoling, et al.
Publicado: (2019)

Utilizing Entity-Based Gated Convolution and Multilevel Sentence Attention to Improve Distantly Supervised Relation Extraction
por: Yi, Qian, et al.
Publicado: (2021)

Application of unsupervised deep learning algorithms for identification of specific clusters of chronic cough patients from EMR data
por: Shao, Wei, et al.
Publicado: (2022)

EMR in Eye Units
por: Camburu, Georgiana, et al.
Publicado: (2020)

Relation extraction in Chinese using attention-based bidirectional long short-term memory networks
por: Zhang, Yanzi
Publicado: (2023)

EXTraction of EMR numerical data: an efficient and generalizable tool to EXTEND clinical research
por: Cai, Tianrun, et al.
Publicado: (2019)

Clinical Named Entity Recognition from Chinese Electronic Medical Records Based on Deep Learning Pretraining
por: Gong, Lejun, et al.
Publicado: (2020)

Predicting protein residue-residue contacts using random forests and deep networks
por: Luttrell, Joseph, et al.
Publicado: (2019)

The Comparative Experimental Study of Multilabel Classification for Diagnosis Assistant Based on Chinese Obstetric EMRs
por: Zhang, Kunli, et al.
Publicado: (2018)

The ‘Anchoring-EMR’ technique has already been described and named the ‘Tip-in EMR’ technique
por: Imai, Kenichiro, et al.
Publicado: (2020)

Combining structured and unstructured data in EMRs to create clinically-defined EMR-derived cohorts
por: Tam, Charmaine S., et al.
Publicado: (2021)

Recognition of Rare Microfossils Using Transfer Learning and Deep Residual Networks
por: Wang, Bin, et al.
Publicado: (2022)

An Entity Relation Extraction Method for Few-Shot Learning on the Food Health and Safety Domain
por: Zuo, Min, et al.
Publicado: (2022)

Immunization registries in the EMR Era
por: Stevens, Lindsay A., et al.
Publicado: (2013)

Asymmetric protonation of EmrE
por: Morrison, Emma A., et al.
Publicado: (2015)

An image caption model based on attention mechanism and deep reinforcement learning
por: Bai, Tong, et al.
Publicado: (2023)

RTJTN: Relational Triplet Joint Tagging Network for Joint Entity and Relation Extraction
por: Yang, Zhenyu, et al.
Publicado: (2021)

An imConvNet-based deep learning model for Chinese medical named entity recognition
por: Zheng, Yuchen, et al.
Publicado: (2022)

Radar Human Activity Recognition with an Attention-Based Deep Learning Network
por: Huan, Sha, et al.
Publicado: (2023)

Prescription Extraction from Clinical Notes: Towards Automating EMR Medication Reconciliation
por: Wang, Yajuan, et al.
Publicado: (2015)

Deep Residual Network in Network
por: Alaeddine, Hmidi, et al.
Publicado: (2021)

EmrR-Dependent Upregulation of the Efflux Pump EmrCAB Contributes to Antibiotic Resistance in Chromobacterium violaceum
por: Barroso, Kelly C. M., et al.
Publicado: (2018)

Span-based single-stage joint entity-relation extraction model
por: Han, Dongchen, et al.
Publicado: (2023)

Extraction of entity relations from Chinese medical literature based on multi-scale CRNN
por: Chen, Tingyin, et al.
Publicado: (2022)

Deep Learning Anomaly Classification Using Multi-Attention Residual Blocks for Industrial Control Systems
por: Jiang, Jehn-Ruey, et al.
Publicado: (2022)

A residual-based deep learning approach for ghost imaging
por: Bian, Tong, et al.
Publicado: (2020)

Deep learning for named entity recognition on Chinese electronic medical records: Combining deep transfer learning with multitask bi-directional LSTM RNN
por: Dong, Xishuang, et al.
Publicado: (2019)

Attention Module Magnetic Flux Leakage Linked Deep Residual Network for Pipeline In-Line Inspection
por: Liu, Shucong, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_mb7m4gnt16lsid5pe7og6aho6o