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...

Descripció completa

Guardat en:
Dades bibliogràfiques
Publicat a:Sci Rep
Autors principals: 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
Format: Artigo
Idioma:Inglês
Publicat: Nature Publishing Group UK 2021
Matèries:
Article
Accés en línia: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
Etiquetes: Afegir etiqueta
Sense etiquetes, Sigues el primer a etiquetar aquest registre!

Ítems similars