Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning

The early detection and accurate histopathological diagnosis of gastric cancer are essential factors that can help increase the chances of successful treatment. Here, the authors report on a digital pathology tool achieving high performance on a real world test dataset and show that the system can a...

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Autores principales:	Zhigang Song, Shuangmei Zou, Weixun Zhou, Yong Huang, Liwei Shao, Jing Yuan, Xiangnan Gou, Wei Jin, Zhanbo Wang, Xin Chen, Xiaohui Ding, Jinhong Liu, Chunkai Yu, Calvin Ku, Cancheng Liu, Zhuo Sun, Gang Xu, Yuefeng Wang, Xiaoqing Zhang, Dandan Wang, Shuhao Wang, Wei Xu, Richard C. Davis, Huaiyin Shi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/67894aca423044e8966085a1a7cd5193
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spelling	oai:doaj.org-article:67894aca423044e8966085a1a7cd51932021-12-02T18:53:11ZClinically applicable histopathological diagnosis system for gastric cancer detection using deep learning10.1038/s41467-020-18147-82041-1723https://doaj.org/article/67894aca423044e8966085a1a7cd51932020-08-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18147-8https://doaj.org/toc/2041-1723The early detection and accurate histopathological diagnosis of gastric cancer are essential factors that can help increase the chances of successful treatment. Here, the authors report on a digital pathology tool achieving high performance on a real world test dataset and show that the system can aid pathologists in improving diagnostic accuracy.Zhigang SongShuangmei ZouWeixun ZhouYong HuangLiwei ShaoJing YuanXiangnan GouWei JinZhanbo WangXin ChenXiaohui DingJinhong LiuChunkai YuCalvin KuCancheng LiuZhuo SunGang XuYuefeng WangXiaoqing ZhangDandan WangShuhao WangWei XuRichard C. DavisHuaiyin ShiNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Zhigang Song Shuangmei Zou Weixun Zhou Yong Huang Liwei Shao Jing Yuan Xiangnan Gou Wei Jin Zhanbo Wang Xin Chen Xiaohui Ding Jinhong Liu Chunkai Yu Calvin Ku Cancheng Liu Zhuo Sun Gang Xu Yuefeng Wang Xiaoqing Zhang Dandan Wang Shuhao Wang Wei Xu Richard C. Davis Huaiyin Shi Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
description	The early detection and accurate histopathological diagnosis of gastric cancer are essential factors that can help increase the chances of successful treatment. Here, the authors report on a digital pathology tool achieving high performance on a real world test dataset and show that the system can aid pathologists in improving diagnostic accuracy.
format	article
author	Zhigang Song Shuangmei Zou Weixun Zhou Yong Huang Liwei Shao Jing Yuan Xiangnan Gou Wei Jin Zhanbo Wang Xin Chen Xiaohui Ding Jinhong Liu Chunkai Yu Calvin Ku Cancheng Liu Zhuo Sun Gang Xu Yuefeng Wang Xiaoqing Zhang Dandan Wang Shuhao Wang Wei Xu Richard C. Davis Huaiyin Shi
author_facet	Zhigang Song Shuangmei Zou Weixun Zhou Yong Huang Liwei Shao Jing Yuan Xiangnan Gou Wei Jin Zhanbo Wang Xin Chen Xiaohui Ding Jinhong Liu Chunkai Yu Calvin Ku Cancheng Liu Zhuo Sun Gang Xu Yuefeng Wang Xiaoqing Zhang Dandan Wang Shuhao Wang Wei Xu Richard C. Davis Huaiyin Shi
author_sort	Zhigang Song
title	Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
title_short	Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
title_full	Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
title_fullStr	Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
title_full_unstemmed	Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
title_sort	clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/67894aca423044e8966085a1a7cd5193
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Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning

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