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Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
Lung cancer is the most prevalent cancer worldwide, and histopathological assessment is indispensable for its diagnosis. However, human evaluation of pathology slides cannot accurately predict patients' prognoses. In this study, we obtain 2,186 haematoxylin and eosin stained histopathology whol...
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| Publicado no: | Nat Commun |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4990706/ https://ncbi.nlm.nih.gov/pubmed/27527408 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/ncomms12474 |
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