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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...
Autores principales: | 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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886858/ https://www.ncbi.nlm.nih.gov/pubmed/33594116 http://dx.doi.org/10.1038/s41598-021-83141-z |
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