Cargando…
Independent test of a model to predict severe acute esophagitis
PURPOSE: Treatment planning factors are known to affect the risk of severe acute esophagitis during thoracic radiation therapy. We tested a previously published model to predict the risk of severe acute esophagitis on an independent data set. METHODS AND MATERIALS: The data set consists of data from...
Autores principales: | Huang, Ellen X., Robinson, Clifford G., Molotievschi, Alerson, Bradley, Jeffrey D., Deasy, Joseph O., Oh, Jung Hun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5514225/ https://www.ncbi.nlm.nih.gov/pubmed/28740914 http://dx.doi.org/10.1016/j.adro.2016.11.003 |
Ejemplares similares
-
Simulating intrafraction prostate motion with a random walk model
por: Pommer, Tobias, et al.
Publicado: (2017) -
Incidence and Dosimetric Predictors of Radiation-Induced Gastric Bleeding After Chemoradiation for Esophageal and Gastroesophageal Junction Cancer
por: Montovano, Margaret, et al.
Publicado: (2021) -
Improved prediction of drug-induced liver injury literature using natural language processing and machine learning methods
por: Oh, Jung Hun, et al.
Publicado: (2023) -
Inference of radio-responsive gene regulatory networks using the graphical lasso algorithm
por: Oh, Jung Hun, et al.
Publicado: (2014) -
Identification of biological correlates associated with respiratory failure in COVID-19
por: Oh, Jung Hun, et al.
Publicado: (2020)