Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings
Abstract Computer-assisted reporting (CAR) tools were suggested to improve radiology report quality by context-sensitively recommending key imaging biomarkers. However, studies evaluating machine learning (ML) algorithms on cross-lingual ontological (RadLex) mappings for developing embedded CAR algo...
Guardado en:
Autores principales: | Máté E. Maros, Chang Gyu Cho, Andreas G. Junge, Benedikt Kämpgen, Victor Saase, Fabian Siegel, Frederik Trinkmann, Thomas Ganslandt, Christoph Groden, Holger Wenz |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/12348a5318d740d1a6395bfc7358ede7 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Automatic RadLex coding of Chinese structured radiology reports based on text similarity ensemble
por: Yani Chen, et al.
Publicado: (2021) -
Vera lex
Publicado: (1980) -
El Principio de Jurisdicción Internacional: ¿Lex Lata o Lex Desiderata?
por: Salinas Burgos,Hernán
Publicado: (2007) -
Artificial Neural Network-Derived Cerebral Metabolic Rate of Oxygen for Differentiating Glioblastoma and Brain Metastasis in MRI: A Feasibility Study
por: Hakim Baazaoui, et al.
Publicado: (2021) -
Estudios sobre lex mercatoria una realidad internacional /
Publicado: (2006)