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A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme
Traditional radiomics models mainly rely on explicitly-designed handcrafted features from medical images. This paper aimed to investigate if deep features extracted via transfer learning can generate radiomics signatures for prediction of overall survival (OS) in patients with Glioblastoma Multiform...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5583361/ https://www.ncbi.nlm.nih.gov/pubmed/28871110 http://dx.doi.org/10.1038/s41598-017-10649-8 |