Automatic RadLex coding of Chinese structured radiology reports based on text similarity ensemble
Abstract Background Standardized coding of plays an important role in radiology reports’ secondary use such as data analytics, data-driven decision support, and personalized medicine. RadLex, a standard radiological lexicon, can reduce subjective variability and improve clarity in radiology reports....
Guardado en:
Autores principales: | Yani Chen, Shan Nan, Qi Tian, Hailing Cai, Huilong Duan, Xudong Lu |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
BMC
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/28a3f7883cbc4a23bbeec743bcbee2bd |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Accurate Single-Cell Clustering through Ensemble Similarity Learning
por: Hyundoo Jeong, et al.
Publicado: (2021) -
Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings
por: Máté E. Maros, et al.
Publicado: (2021) -
Application Of Machine Learning Methods To Compare Disciplines Content Using Text Data
por: Roman Kupriyanov, et al.
Publicado: (2021) -
MBD Based 3D CAD Model Automatic Feature Recognition and Similarity Evaluation
por: Shuhui Ding, et al.
Publicado: (2021) -
A Survey of Automatic Text Summarization: Progress, Process and Challenges
por: M. F. Mridha, et al.
Publicado: (2021)