Cargando…
Semantic categorization of Chinese eligibility criteria in clinical trials using machine learning methods
BACKGROUND: Semantic categorization analysis of clinical trials eligibility criteria based on natural language processing technology is crucial for the task of optimizing clinical trials design and building automated patient recruitment system. However, most of related researches focused on English...
Autores principales: | Zong, Hui, Yang, Jinxuan, Zhang, Zeyu, Li, Zuofeng, Zhang, Xiaoyan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050926/ https://www.ncbi.nlm.nih.gov/pubmed/33858409 http://dx.doi.org/10.1186/s12911-021-01487-w |
Ejemplares similares
-
Age-Related Degree and Criteria Differences in Semantic Categorization
por: Verheyen, Steven, et al.
Publicado: (2019) -
Machine learning enabled subgroup analysis with real-world data to inform clinical trial eligibility criteria design
por: Xu, Jie, et al.
Publicado: (2023) -
Analysis of Eligibility Criteria Complexity in Clinical Trials
por: Ross, Jessica, et al.
Publicado: (2010) -
Corpus-based Approach to Creating a Semantic Lexicon for Clinical Research Eligibility Criteria from UMLS
por: Luo, Zhihui, et al.
Publicado: (2010) -
Automated classification of clinical trial eligibility criteria text based on ensemble learning and metric learning
por: Zeng, Kun, et al.
Publicado: (2021)