Application of artificial intelligence in the diagnosis and prediction of gastric cancer

doi:10.35712/aig.v1.i1.12

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Jul 28, 2020 (publication date) through May 10, 2024

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Artificial Intelligence in Gastroenterology

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2644-3236

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

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Artif Intell Gastroenterol. Jul 28, 2020; 1(1): 12-18
Published online Jul 28, 2020. doi: 10.35712/aig.v1.i1.12

Table 1 Application of artificial intelligence in endoscopic images of gastric cancer

Ref.	Images	Sensitivity	Specificity	Accuracy
Hirasawa et al[12]	Endoscopic images with NBI imaging	92.20%	-	30.60 %
Zhu et al[14]	Endoscopic images	76.47%	95.56%	89.16%
Li et al[15]	ME-NBI images	91.18%	90.64%	90.91%
Horiuchi et al[16]	ME-NBI images	95.40%	71.00%	85.30%

NBI: Narrow band imaging; ME-NBI: Magnifying endoscopy with narrow band imaging.

Citation: Qie YY, Xue XF, Wang XG, Dang SC. Application of artificial intelligence in the diagnosis and prediction of gastric cancer. Artif Intell Gastroenterol 2020; 1(1): 12-18
URL: https://www.wjgnet.com/2644-3236/full/v1/i1/12.htm
DOI: https://dx.doi.org/10.35712/aig.v1.i1.12