Cargando…
CNN-based ranking for biomedical entity normalization
BACKGROUND: Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that...
Autores principales: | Li, Haodi, Chen, Qingcai, Tang, Buzhou, Wang, Xiaolong, Xu, Hua, Wang, Baohua, Huang, Dong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629610/ https://www.ncbi.nlm.nih.gov/pubmed/28984180 http://dx.doi.org/10.1186/s12859-017-1805-7 |
Ejemplares similares
-
Entity recognition in Chinese clinical text using attention-based CNN-LSTM-CRF
por: Tang, Buzhou, et al.
Publicado: (2019) -
Evaluating Word Representation Features in Biomedical Named Entity Recognition Tasks
por: Tang, Buzhou, et al.
Publicado: (2014) -
Improving deep learning method for biomedical named entity recognition by using entity definition information
por: Xiong, Ying, et al.
Publicado: (2021) -
Temporal indexing of medical entity in Chinese clinical notes
por: Liu, Zengjian, et al.
Publicado: (2019) -
HITSZ_CDR: an end-to-end chemical and disease relation extraction system for BioCreative V
por: Li, Haodi, et al.
Publicado: (2016)