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Cited by in CrossRef
For: Jang HJ, Lee A, Kang J, Song IH, Lee SH. Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach. World J Gastroenterol 2021; 27(44): 7687-7704 [PMID: 34908807 DOI: 10.3748/wjg.v27.i44.7687]
URL: https://www.wjgnet.com/1007-9327/full/v27/i44/7687.htm
Number Citing Articles
1
Trinh Thi Le Vuong, Boram Song, Jin T. Kwak, Kyungeun Kim. Prediction of Epstein-Barr Virus Status in Gastric Cancer Biopsy Specimens Using a Deep Learning AlgorithmJAMA Network Open 2022; 5(10): e2236408 doi: 10.1001/jamanetworkopen.2022.36408
2
Sung Hak Lee, Yujin Lee, Hyun‐Jong Jang. Deep learning captures selective features for discrimination of microsatellite instability from pathologic tissue slides of gastric cancerInternational Journal of Cancer 2023; 152(2): 298 doi: 10.1002/ijc.34251
3
Hyun-Jong Jang, Jai-Hyang Go, Younghoon Kim, Sung Hak Lee. Deep Learning for the Pathologic Diagnosis of Hepatocellular Carcinoma, Cholangiocarcinoma, and Metastatic Colorectal CancerCancers 2023; 15(22): 5389 doi: 10.3390/cancers15225389
4
Sung Hak Lee, Hyun-Jong Jang. Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncologyClinical and Molecular Hepatology 2022; 28(4): 754 doi: 10.3350/cmh.2021.0394
5
Heather D. Couture. Deep Learning-Based Prediction of Molecular Tumor Biomarkers from H&E: A Practical ReviewJournal of Personalized Medicine 2022; 12(12): 2022 doi: 10.3390/jpm12122022
6
Zihan Chen, Xingyu Li, Miaomiao Yang, Hong Zhang, Xu Steven Xu. Optimization of deep learning models for the prediction of gene mutations using unsupervised clusteringThe Journal of Pathology: Clinical Research 2023; 9(1): 3 doi: 10.1002/cjp2.302
7
Zheng Wei, Xu Zhao, Jing Chen, Qiuyan Sun, Zeyang Wang, Yanli Wang, Zhiyi Ye, Yuan Yuan, Liping Sun, Jingjing Jing. Deep Learning–Based Stratification of Gastric Cancer Patients from Hematoxylin and Eosin–Stained Whole Slide Images by Predicting Molecular Features for Immunotherapy ResponseThe American Journal of Pathology 2023; 193(10): 1517 doi: 10.1016/j.ajpath.2023.06.004
8
Jiefeng Gan, Hanchen Wang, Hui Yu, Zitong He, Wenjuan Zhang, Ke Ma, Lianghui Zhu, Yutong Bai, Zongwei Zhou, Alan Yullie, Xiang Bai, Mingwei Wang, Dehua Yang, Yanyan Chen, Guoan Chen, Joan Lasenby, Chao Cheng, Jia Wu, Jianjun Zhang, Xinggang Wang, Yaobing Chen, Guoping Wang, Tian Xia. Focalizing regions of biomarker relevance facilitates biomarker prediction on histopathological imagesiScience 2023; 26(10): 107243 doi: 10.1016/j.isci.2023.107243
9
Sarah Fremond, Viktor Hendrik Koelzer, Nanda Horeweg, Tjalling Bosse. The evolving role of morphology in endometrial cancer diagnostics: From histopathology and molecular testing towards integrative data analysis by deep learningFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.928977
10
Aysen Yavuz, Anil Alpsoy, Elif Ocak Gedik, Mennan Yigitcan Celik, Cumhur Ibrahim Bassorgun, Betul Unal, Gulsum Ozlem Elpek. Artificial intelligence applications in predicting the behavior of gastrointestinal cancers in pathologyArtificial Intelligence in Gastroenterology 2022; 3(5): 142-162 doi: 10.35712/aig.v3.i5.142