Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI

Glioblastoma (GBM) is a heterogeneous and lethal brain cancer. These tumors are followed using magnetic resonance imaging (MRI), which is unable to precisely identify tumor cell invasion, impairing effective surgery and radiation planning. We present a novel hybrid model, based on multiparametric in...

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Detalhes bibliográficos
Publicado no:Sci Rep
Main Authors: Gaw, Nathan, Hawkins-Daarud, Andrea, Hu, Leland S., Yoon, Hyunsoo, Wang, Lujia, Xu, Yanzhe, Jackson, Pamela R., Singleton, Kyle W., Baxter, Leslie C., Eschbacher, Jennifer, Gonzales, Ashlyn, Nespodzany, Ashley, Smith, Kris, Nakaji, Peter, Mitchell, J. Ross, Wu, Teresa, Swanson, Kristin R., Li, Jing
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2019
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6624304/
https://ncbi.nlm.nih.gov/pubmed/31296889
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-46296-4
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