Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma

Translocation renal cell carcinoma is an aggressive form of renal cancer that is often misdiagnosed to other subtypes. Here the authors demonstrated that by using machine learning and H&E stained whole-slide images, an accurate diagnose of this particular type of renal cancer can be achieved.

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Autores principales:	Jun Cheng, Zhi Han, Rohit Mehra, Wei Shao, Michael Cheng, Qianjin Feng, Dong Ni, Kun Huang, Liang Cheng, Jie Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/72fbcd5316984ef68d80cb64d0e5b548
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spelling	oai:doaj.org-article:72fbcd5316984ef68d80cb64d0e5b5482021-12-02T14:40:30ZComputational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma10.1038/s41467-020-15671-52041-1723https://doaj.org/article/72fbcd5316984ef68d80cb64d0e5b5482020-04-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-15671-5https://doaj.org/toc/2041-1723Translocation renal cell carcinoma is an aggressive form of renal cancer that is often misdiagnosed to other subtypes. Here the authors demonstrated that by using machine learning and H&E stained whole-slide images, an accurate diagnose of this particular type of renal cancer can be achieved.Jun ChengZhi HanRohit MehraWei ShaoMichael ChengQianjin FengDong NiKun HuangLiang ChengJie ZhangNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jun Cheng Zhi Han Rohit Mehra Wei Shao Michael Cheng Qianjin Feng Dong Ni Kun Huang Liang Cheng Jie Zhang Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma
description	Translocation renal cell carcinoma is an aggressive form of renal cancer that is often misdiagnosed to other subtypes. Here the authors demonstrated that by using machine learning and H&E stained whole-slide images, an accurate diagnose of this particular type of renal cancer can be achieved.
format	article
author	Jun Cheng Zhi Han Rohit Mehra Wei Shao Michael Cheng Qianjin Feng Dong Ni Kun Huang Liang Cheng Jie Zhang
author_facet	Jun Cheng Zhi Han Rohit Mehra Wei Shao Michael Cheng Qianjin Feng Dong Ni Kun Huang Liang Cheng Jie Zhang
author_sort	Jun Cheng
title	Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma
title_short	Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma
title_full	Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma
title_fullStr	Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma
title_full_unstemmed	Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma
title_sort	computational analysis of pathological images enables a better diagnosis of tfe3 xp11.2 translocation renal cell carcinoma
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/72fbcd5316984ef68d80cb64d0e5b548
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Computational analysis of pathological images enables a better diagnosis of TFE3 Xp11.2 translocation renal cell carcinoma

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