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Cited by in F6Publishing
For: Yoon HJ, Kim JH. Lesion-Based Convolutional Neural Network in Diagnosis of Early Gastric Cancer. Clin Endosc. 2020;53:127-131. [PMID: 32252505 DOI: 10.5946/ce.2020.046] [Cited by in Crossref: 15] [Cited by in F6Publishing: 9] [Article Influence: 7.5] [Reference Citation Analysis]
Number Citing Articles
1 Kim JH, Nam SJ, Park SC. Usefulness of artificial intelligence in gastric neoplasms. World J Gastroenterol 2021; 27(24): 3543-3555 [PMID: 34239268 DOI: 10.3748/wjg.v27.i24.3543] [Cited by in CrossRef: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Zhang M, Zhu C, Wang Y, Kong Z, Hua Y, Zhang W, Si X, Ye B, Xu X, Li L, Heng D, Liu B, Tian S, Wu J, Dang Y, Zhang G. Differential diagnosis for esophageal protruded lesions using a deep convolution neural network in endoscopic images. Gastrointest Endosc 2021;93:1261-1272.e2. [PMID: 33065026 DOI: 10.1016/j.gie.2020.10.005] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Hashemzadeh H, Shojaeilangari S, Allahverdi A, Rothbauer M, Ertl P, Naderi-Manesh H. A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications. Sci Rep 2021;11:9804. [PMID: 33963232 DOI: 10.1038/s41598-021-89352-8] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
4 Bhardwaj P, Bhandari G, Kumar Y, Gupta S. An Investigational Approach for the Prediction of Gastric Cancer Using Artificial Intelligence Techniques: A Systematic Review. Arch Computat Methods Eng. [DOI: 10.1007/s11831-022-09737-4] [Reference Citation Analysis]
5 Paderno A, Holsinger FC, Piazza C. Videomics: bringing deep learning to diagnostic endoscopy. Curr Opin Otolaryngol Head Neck Surg 2021;29:143-8. [PMID: 33595977 DOI: 10.1097/MOO.0000000000000697] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
6 Huang D, Bai H, Wang L, Hou Y, Li L, Xia Y, Yan Z, Chen W, Chang L, Li W. The Application and Development of Deep Learning in Radiotherapy: A Systematic Review. Technol Cancer Res Treat 2021;20:15330338211016386. [PMID: 34142614 DOI: 10.1177/15330338211016386] [Reference Citation Analysis]
7 Kim KO, Kim EY. Application of Artificial Intelligence in the Detection and Characterization of Colorectal Neoplasm. Gut Liver. 2021;15:346-353. [PMID: 32773386 DOI: 10.5009/gnl20186] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 [DOI: 10.1109/csrswtc50769.2020.9372583] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
9 Yao Z, Jin T, Mao B, Lu B, Zhang Y, Li S, Chen W. Construction and Multicenter Diagnostic Verification of Intelligent Recognition System for Endoscopic Images From Early Gastric Cancer Based on YOLO-V3 Algorithm. Front Oncol 2022;12:815951. [DOI: 10.3389/fonc.2022.815951] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Shi XJ, Wei Y, Ji B. Systems Biology of Gastric Cancer: Perspectives on the Omics-Based Diagnosis and Treatment.Front Mol Biosci. 2020;7:203. [PMID: 33005629 DOI: 10.3389/fmolb.2020.00203] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 1.5] [Reference Citation Analysis]