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Cited by in F6Publishing
For: Wang X, Chen Y, Gao Y, Zhang H, Guan Z, Dong Z, Zheng Y, Jiang J, Yang H, Wang L, Huang X, Ai L, Yu W, Li H, Dong C, Zhou Z, Liu X, Yu G. Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning. Nat Commun 2021;12:1637. [PMID: 33712598 DOI: 10.1038/s41467-021-21674-7] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
Number Citing Articles
1 Zheng H, Zhao J, Wang X, Yan S, Chu H, Gao M, Zhang X. Integrated Pipeline of Rapid Isolation and Analysis of Human Plasma Exosomes for Cancer Discrimination Based on Deep Learning of MALDI-TOF MS Fingerprints. Anal Chem 2022. [PMID: 35025210 DOI: 10.1021/acs.analchem.1c04762] [Reference Citation Analysis]
2 Klein S, Duda DG. Machine Learning for Future Subtyping of the Tumor Microenvironment of Gastro-Esophageal Adenocarcinomas. Cancers (Basel) 2021;13:4919. [PMID: 34638408 DOI: 10.3390/cancers13194919] [Reference Citation Analysis]
3 Zhuang H, Zhang J, Liao F. A systematic review on application of deep learning in digestive system image processing. Vis Comput 2021;:1-16. [PMID: 34744231 DOI: 10.1007/s00371-021-02322-z] [Reference Citation Analysis]
4 Hinata M, Ushiku T. Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning. Sci Rep 2021;11:22636. [PMID: 34811485 DOI: 10.1038/s41598-021-02168-4] [Reference Citation Analysis]
5 Zhang X, Zhang Y, Zhang G, Qiu X, Tan W, Yin X, Liao L. Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential. Front Oncol 2022;12:773840. [DOI: 10.3389/fonc.2022.773840] [Reference Citation Analysis]
6 Huang B, Tian S, Zhan N, Ma J, Huang Z, Zhang C, Zhang H, Ming F, Liao F, Ji M, Zhang J, Liu Y, He P, Deng B, Hu J, Dong W. Accurate diagnosis and prognosis prediction of gastric cancer using deep learning on digital pathological images: A retrospective multicentre study. EBioMedicine 2021;73:103631. [PMID: 34678610 DOI: 10.1016/j.ebiom.2021.103631] [Reference Citation Analysis]