Nature Communications (Aug 2020)
Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
- 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
Affiliations
- Zhigang Song
- Department of Pathology, The Chinese PLA General Hospital
- Shuangmei Zou
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
- Weixun Zhou
- Department of Pathology, Peking Union Medical College Hospital
- Yong Huang
- Department of Pathology, The Chinese PLA General Hospital
- Liwei Shao
- Department of Pathology, The Chinese PLA General Hospital
- Jing Yuan
- Department of Pathology, The Chinese PLA General Hospital
- Xiangnan Gou
- Department of Pathology, The Chinese PLA General Hospital
- Wei Jin
- Department of Pathology, The Chinese PLA General Hospital
- Zhanbo Wang
- Department of Pathology, The Chinese PLA General Hospital
- Xin Chen
- Department of Pathology, The Chinese PLA General Hospital
- Xiaohui Ding
- Department of Pathology, The Chinese PLA General Hospital
- Jinhong Liu
- Department of Pathology, The Chinese PLA General Hospital
- Chunkai Yu
- Department of Pathology, Beijing Shijitan Hospital, Capital Medical University
- Calvin Ku
- Thorough Images
- Cancheng Liu
- Thorough Images
- Zhuo Sun
- Thorough Images
- Gang Xu
- Thorough Images
- Yuefeng Wang
- Thorough Images
- Xiaoqing Zhang
- Thorough Images
- Dandan Wang
- Department of Pathology, Third Hospital, School of Basic Medical Sciences, Peking University Health Science Center
- Shuhao Wang
- Thorough Images
- Wei Xu
- Institute for Interdisciplinary Information Sciences, Tsinghua University
- Richard C. Davis
- Department of Pathology, Duke University Medical Center
- Huaiyin Shi
- Department of Pathology, The Chinese PLA General Hospital
- DOI
- https://doi.org/10.1038/s41467-020-18147-8
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 9
Abstract
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.
