Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma

Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision m...

ver descrição completa

Na minha lista:
Detalhes bibliográficos
Publicado no:Sci Rep
Main Authors: Hu, Leland S., Wang, Lujia, Hawkins-Daarud, Andrea, Eschbacher, Jennifer M., Singleton, Kyle W., Jackson, Pamela R., Clark-Swanson, Kamala, Sereduk, Christopher P., Peng, Sen, Wang, Panwen, Wang, Junwen, Baxter, Leslie C., Smith, Kris A., Mazza, Gina L., Stokes, Ashley M., Bendok, Bernard R., Zimmerman, Richard S., Krishna, Chandan, Porter, Alyx B., Mrugala, Maciej M., Hoxworth, Joseph M., Wu, Teresa, Tran, Nhan L., Swanson, Kristin R., Li, Jing
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2021
Assuntos:
Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7886858/
https://ncbi.nlm.nih.gov/pubmed/33594116
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-021-83141-z
Tags: Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!

Registos relacionados