Cargando…
Incorporating Domain Knowledge Into Language Models by Using Graph Convolutional Networks for Assessing Semantic Textual Similarity: Model Development and Performance Comparison
BACKGROUND: Although electronic health record systems have facilitated clinical documentation in health care, they have also introduced new challenges, such as the proliferation of redundant information through the use of copy and paste commands or templates. One approach to trimming down bloated cl...
Autores principales: | Chang, David, Lin, Eric, Brandt, Cynthia, Taylor, Richard Andrew |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8665398/ https://www.ncbi.nlm.nih.gov/pubmed/34842531 http://dx.doi.org/10.2196/23101 |
Ejemplares similares
-
Semantic Textual Similarity in Japanese Clinical Domain Texts Using BERT
por: Mutinda, Faith Wavinya, et al.
Publicado: (2021) -
Path-based knowledge reasoning with textual semantic information for medical knowledge graph completion
por: Lan, Yinyu, et al.
Publicado: (2021) -
Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study
por: Chen, Qingyu, et al.
Publicado: (2021) -
Semantic similarity in the biomedical domain: an evaluation across knowledge sources
por: Garla, Vijay N, et al.
Publicado: (2012) -
Measurement of Semantic Textual Similarity in Clinical Texts: Comparison of Transformer-Based Models
por: Yang, Xi, et al.
Publicado: (2020)