Cargando…

A semi-supervised approach for extracting TCM clinical terms based on feature words

BACKGROUND: A semi-supervised model is proposed for extracting clinical terms of Traditional Chinese Medicine using feature words. METHODS: The extraction model is based on BiLSTM-CRF and combined with semi-supervised learning and feature word set, which reduces the cost of manual annotation and lev...

Descripción completa

Detalles Bibliográficos
Autores principales:	Liu, Liangliang, Wu, Xiaojing, Liu, Hui, Cao, Xinyu, Wang, Haitao, Zhou, Hongwei, Xie, Qi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2020
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477860/ https://www.ncbi.nlm.nih.gov/pubmed/32646408 http://dx.doi.org/10.1186/s12911-020-1108-1

Ejemplares similares

Generative Adversarial Training for Supervised and Semi-supervised Learning
por: Wang, Xianmin, et al.
Publicado: (2022)

Semi-Supervised Fuzzy Clustering with Feature Discrimination
por: Li, Longlong, et al.
Publicado: (2015)

Simple strategies for semi-supervised feature selection
por: Sechidis, Konstantinos, et al.
Publicado: (2017)

Semi-supervised method for biomedical event extraction
por: Wang, Jian, et al.
Publicado: (2013)

Semi-Supervised Feature Transformation for Tissue Image Classification
por: Watanabe, Kenji, et al.
Publicado: (2016)

Sintering Quality Prediction Model Based on Semi-Supervised Dynamic Time Feature Extraction Framework
por: Li, Yuxuan, et al.
Publicado: (2022)

AGREE II for TCM: Tailored to evaluate methodological quality of TCM clinical practice guidelines
por: Xie, Xiuli, et al.
Publicado: (2023)

Feature selection and semi-supervised clustering using multiobjective optimization
por: Saha, Sriparna, et al.
Publicado: (2014)

Semi-supervised learning /
Publicado: (2010)

Semi-Supervised Instance-Segmentation Model for Feature Transfer Based on Category Attention
por: Wang, Hao, et al.
Publicado: (2022)

TCM
por: Stockert, Karin
Publicado: (2020)

Robust and accurate pulmonary nodule detection with self-supervised feature learning on domain adaptation
por: Liu, Jingya, et al.
Publicado: (2022)

A supervised scheme for aspect extraction in sentiment analysis using the hybrid feature set of word dependency relations and lemmas
por: Bhamare, Bhavana R., et al.
Publicado: (2021)

Semi-supervised method for image texture classification of pituitary tumors via CycleGAN and optimized feature extraction
por: Zhu, Hong, et al.
Publicado: (2020)

Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM
por: Liu, Chengyin, et al.
Publicado: (2019)

Direct comparison of supervised and semi-supervised retraining approaches for co-adaptive BCIs
por: Schwarz, Andreas, et al.
Publicado: (2019)

Semi-supervised Extractive Question Summarization Using Question-Answer Pairs
por: Machida, Kazuya, et al.
Publicado: (2020)

Semi-CAM: A semi-supervised deconvolution method for bulk transcriptomic data with partial marker gene information
por: Dong, Li, et al.
Publicado: (2020)

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

Stockwell transform and semi-supervised feature selection from deep features for classification of BCI signals
por: Salimpour, Sahar, et al.
Publicado: (2022)

Supervised, semi-supervised and unsupervised inference of gene regulatory networks
por: Maetschke, Stefan R., et al.
Publicado: (2014)

Self-supervised Learning for Semi-supervised Time Series Classification
por: Jawed, Shayan, et al.
Publicado: (2020)

Multi-Scale Aggregation Graph Neural Networks Based on Feature Similarity for Semi-Supervised Learning
por: Zhang, Xun, et al.
Publicado: (2021)

Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction mention extraction
por: Gupta, Shashank, et al.
Publicado: (2018)

Semi-supervised discovery of differential genes
por: Oba, Shigeyuki, et al.
Publicado: (2006)

Semi-supervised protein subcellular localization
por: Xu, Qian, et al.
Publicado: (2009)

Semi-supervised classifier guided by discriminator
por: Jamroziński, Sebastian, et al.
Publicado: (2022)

Semi-supervised learning in cancer diagnostics
por: Eckardt, Jan-Niklas, et al.
Publicado: (2022)

Semi-supervised nuclei segmentation based on multi-edge features fusion attention network
por: Li, Huachang, et al.
Publicado: (2023)

Feature-enhanced adversarial semi-supervised semantic segmentation network for pulmonary embolism annotation
por: Cheng, Ting-Wei, et al.
Publicado: (2023)

Editorial: TCM approaches in cellular endocrinology
por: Xu, Jin-Wen
Publicado: (2023)

Data Efficiency Semi-Supervised Meta-Learning Elucidates Understudied Interspecies Molecular Interactions
por: Wu, You, et al.
Publicado: (2023)

Active link selection for efficient semi-supervised community detection
por: Yang, Liang, et al.
Publicado: (2015)

Semi-Supervised Defect Detection Method with Data-Expanding Strategy for PCB Quality Inspection
por: Wan, Yusen, et al.
Publicado: (2022)

Combining active learning and semi-supervised learning techniques to extract protein interaction sentences
por: Song, Min, et al.
Publicado: (2011)

A Novel Semi-Supervised Feature Extraction Method and Its Application in Automotive Assembly Fault Diagnosis Based on Vision Sensor Data
por: Zeng, Xuan, et al.
Publicado: (2018)

Selfee, self-supervised features extraction of animal behaviors
por: Jia, Yinjun, et al.
Publicado: (2022)

TCM-Mesh: The database and analytical system for network pharmacology analysis for TCM preparations
por: Zhang, Run-zhi, et al.
Publicado: (2017)

Differences in medical costs between TCM users and TCM nonusers in inpatients with thalassemia
por: Han, Zhaoran, et al.
Publicado: (2023)

Comparing supervised and semi-supervised Machine Learning Models on Diagnosing Breast Cancer
por: Al-Azzam, Nosayba, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_120d68lq1ab4u4ap4h2rgemfsn