Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach

doi:10.3748/wjg.v27.i44.7687

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Nov 28, 2021 (publication date) through Nov 2, 2024

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastroenterol. Nov 28, 2021; 27(44): 7687-7704
Published online Nov 28, 2021. doi: 10.3748/wjg.v27.i44.7687

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Figure 3 Classification results of ERBB2 gene in the The Cancer Genome Atlas gastric cancer dataset. The configuration of the figure is the same as in Figure 2. A and B: Upper panels are results for the frozen tissue and lower panels; C and D: Results for the formalin-fixed paraffin-embedded tissues. ERBB2-M: ERBB2 mutated, ERBB2-W: ERBB2 wild-type.

Citation: 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
URL: https://www.wjgnet.com/1007-9327/full/v27/i44/7687.htm
DOI: https://dx.doi.org/10.3748/wjg.v27.i44.7687