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Clinical use of machine learning‐based pathomics signature for diagnosis and survival prediction of bladder cancer

Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E‐stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TCGA). We constructed and cross‐verified automat...

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Detalles Bibliográficos
Publicado en:Cancer Sci
Main Authors: Chen, Siteng, Jiang, Liren, Zheng, Xinyi, Shao, Jialiang, Wang, Tao, Zhang, Encheng, Gao, Feng, Wang, Xiang, Zheng, Junhua
Formato: Artigo
Idioma:Inglês
Publicado: John Wiley and Sons Inc. 2021
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Acceso en liña:https://ncbi.nlm.nih.gov/pmc/articles/PMC8253293/
https://ncbi.nlm.nih.gov/pubmed/33931925
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/cas.14927
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