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Radiomics-Based Machine Learning Technology Enables Better Differentiation Between Glioblastoma and Anaplastic Oligodendroglioma
Purpose: The aim of this study was to test whether radiomics-based machine learning can enable the better differentiation between glioblastoma (GBM) and anaplastic oligodendroglioma (AO). Methods: This retrospective study involved 126 patients histologically diagnosed as GBM (n = 76) or AO (n = 50)...
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| Publicat a: | Front Oncol |
|---|---|
| Autors principals: | , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Frontiers Media S.A.
2019
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6848260/ https://ncbi.nlm.nih.gov/pubmed/31750250 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fonc.2019.01164 |
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