Cargando…
Using Character-Level and Entity-Level Representations to Enhance Bidirectional Encoder Representation From Transformers-Based Clinical Semantic Textual Similarity Model: ClinicalSTS Modeling Study
BACKGROUND: With the popularity of electronic health records (EHRs), the quality of health care has been improved. However, there are also some problems caused by EHRs, such as the growing use of copy-and-paste and templates, resulting in EHRs of low quality in content. In order to minimize data red...
Autores principales: | Xiong, Ying, Chen, Shuai, Chen, Qingcai, Yan, Jun, Tang, Buzhou |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7803475/ https://www.ncbi.nlm.nih.gov/pubmed/33372664 http://dx.doi.org/10.2196/23357 |
Ejemplares similares
-
Distributed representation and one-hot representation fusion with gated network for clinical semantic textual similarity
por: Xiong, Ying, et al.
Publicado: (2020) -
Evaluating Word Representation Features in Biomedical Named Entity Recognition Tasks
por: Tang, Buzhou, et al.
Publicado: (2014) -
Adapting Bidirectional Encoder Representations from Transformers (BERT) to Assess Clinical Semantic Textual Similarity: Algorithm Development and Validation Study
por: Kades, Klaus, et al.
Publicado: (2021) -
Temporal indexing of medical entity in Chinese clinical notes
por: Liu, Zengjian, et al.
Publicado: (2019) -
Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features
por: Tang, Buzhou, et al.
Publicado: (2013)