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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’...
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| Publicado no: | Med Biol Eng Comput |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Springer Berlin Heidelberg
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7188709/ https://ncbi.nlm.nih.gov/pubmed/32124225 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11517-020-02147-3 |
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