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 8 Mutation prediction of PIK3CA (A and B) and TP53 (C and D) genes for the SSMH gastric cancer tissue slides by the classifiers trained with both The Cancer Genome Atlas and SSMH data. The configuration of the figure is the same as in figure 7. PIK3CA-M: PIK3CA mutated, PIK3CA-W: PIK3CA wild-type, TP53-M: TP53 mutated, TP53-W: TP53 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