Application of deep learning in image recognition and diagnosis of gastric cancer

doi:10.37126/aige.v2.i2.12

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Apr 28, 2021 (publication date) through Nov 4, 2024

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Artificial Intelligence in Gastrointestinal Endoscopy

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2689-7164

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

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Artif Intell Gastrointest Endosc. Apr 28, 2021; 2(2): 12-24
Published online Apr 28, 2021. doi: 10.37126/aige.v2.i2.12

Table 1 Commonly used databases in image recognition of gastric cancer

Database	Time collected	Number of samples	Resolution	Training set	Test set
GR-AIDS[31]	2019	1036496	512 × 512	829197	103650
Jang Hyung Lee[32]	2019	787	224 × 224	717	70
Toshiaki Hirasawa[33]	2018	13584	512 × 512	13584	2496
Bum-Joo Cho[34]	2019	5017	512 × 512	4205	812
Hiroya Ueyama[35]	2020	7874	512 × 512	5574	2300
Lan Li[36]	2020	2088	512 × 512	1747	341
Mads Sylvest Bergholt[37]	2011	1063	512 × 512	850	213

Citation: Li Y, Zhou D, Liu TT, Shen XZ. Application of deep learning in image recognition and diagnosis of gastric cancer. Artif Intell Gastrointest Endosc 2021; 2(2): 12-24
URL: https://www.wjgnet.com/2689-7164/full/v2/i2/12.htm
DOI: https://dx.doi.org/10.37126/aige.v2.i2.12