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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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Dades bibliogràfiques
Publicat a:Cancer Sci
Autors principals: Chen, Siteng, Jiang, Liren, Zheng, Xinyi, Shao, Jialiang, Wang, Tao, Zhang, Encheng, Gao, Feng, Wang, Xiang, Zheng, Junhua
Format: Artigo
Idioma:Inglês
Publicat: John Wiley and Sons Inc. 2021
Matèries:
Accés en línia: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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