Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia

PURPOSE: The purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP) models based on the mean radiation dose to parotid glands. MATERIAL AN...

Descripción completa

Detalles Bibliográficos
Autores principales: Gabryś, Hubert S., Buettner, Florian, Sterzing, Florian, Hauswald, Henrik, Bangert, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844945/
https://www.ncbi.nlm.nih.gov/pubmed/29556480
http://dx.doi.org/10.3389/fonc.2018.00035

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844945/
https://www.ncbi.nlm.nih.gov/pubmed/29556480
http://dx.doi.org/10.3389/fonc.2018.00035

Ejemplares similares