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DeepSurvNet: deep survival convolutional network for brain cancer survival rate classification based on histopathological images
Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuable information with relation to cancer disease and its clinical outcomes. Still, there are no highly accurate automated methods to correlate histolopathological images with brain cancer patients’...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Berlin Heidelberg
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188709/ https://www.ncbi.nlm.nih.gov/pubmed/32124225 http://dx.doi.org/10.1007/s11517-020-02147-3 |