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Cited by in F6Publishing
For: [DOI: 10.1101/813543] [Cited by in Crossref: 14] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
Number Citing Articles
1 [DOI: 10.1101/554527] [Cited by in Crossref: 11] [Cited by in F6Publishing: 5] [Reference Citation Analysis]
2 [DOI: 10.1101/610311] [Cited by in Crossref: 13] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
3 [DOI: 10.1101/2020.05.15.096628] [Cited by in Crossref: 8] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
4 Jang HJ, Lee A, Kang J, Song IH, Lee SH. Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning. World J Gastroenterol 2020; 26(40): 6207-6223 [PMID: 33177794 DOI: 10.3748/wjg.v26.i40.6207] [Cited by in CrossRef: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
5 [DOI: 10.1101/715656] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
6 Kather JN, Calderaro J. Development of AI-based pathology biomarkers in gastrointestinal and liver cancer. Nat Rev Gastroenterol Hepatol 2020;17:591-2. [DOI: 10.1038/s41575-020-0343-3] [Cited by in Crossref: 8] [Cited by in F6Publishing: 11] [Article Influence: 4.0] [Reference Citation Analysis]
7 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] [Reference Citation Analysis]