Cargando…
Predicting the Local Response of Metastatic Brain Tumor to Gamma Knife Radiosurgery by Radiomics With a Machine Learning Method
PURPOSE: The current study proposed a model to predict the response of brain metastases (BMs) treated by Gamma knife radiosurgery (GKRS) using a machine learning (ML) method with radiomics features. The model can be used as a decision tool by clinicians for the most desirable treatment outcome. METH...
Autores principales: | Kawahara, Daisuke, Tang, Xueyan, Lee, Chung K., Nagata, Yasushi, Watanabe, Yoichi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832385/ https://www.ncbi.nlm.nih.gov/pubmed/33505904 http://dx.doi.org/10.3389/fonc.2020.569461 |
Ejemplares similares
-
BRAF Mutation Is Associated with Improved Local Control of Melanoma Brain Metastases Treated with Gamma Knife Radiosurgery
por: Gallaher, Ian S., et al.
Publicado: (2016) -
Cumulative Doses to Brain and Other Critical Structures After Multisession Gamma Knife Stereotactic Radiosurgery for Treatment of Multiple Metastatic Tumors
por: Yuan, Jianling, et al.
Publicado: (2018) -
Characteristic of Tumor Regrowth After Gamma Knife Radiosurgery and Outcomes of Repeat Gamma Knife Radiosurgery in Nonfunctioning Pituitary Adenomas
por: Li, Yanli, et al.
Publicado: (2021) -
Utilization of CBCT to improve the delivery accuracy of Gamma Knife radiosurgery with G‐frame
por: Claps, Lindsey, et al.
Publicado: (2021) -
Assessment of the accuracy and stability of frameless gamma knife radiosurgery
por: Chung, Hyun‐Tai, et al.
Publicado: (2018)