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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Detalles Bibliográficos
Autores principales: 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: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624304/
https://www.ncbi.nlm.nih.gov/pubmed/31296889
http://dx.doi.org/10.1038/s41598-019-46296-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6624304/
https://www.ncbi.nlm.nih.gov/pubmed/31296889
http://dx.doi.org/10.1038/s41598-019-46296-4

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