Application of endoscopic ultrasonography for detecting esophageal lesions based on convolutional neural network

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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. Jun 14, 2022; 28(22): 2457-2467
Published online Jun 14, 2022. doi: 10.3748/wjg.v28.i22.2457

Table 1 Statistics distribution from esophageal lesion database

	Lesions invading the submucosa and muscularis mucosae	Lesions invading the muscularis propria	Lesions invading the serosal layer
Train	473	376	74
Validation	59	47	9
Test	59	47	9
Total	591	470	92

Citation: Liu GS, Huang PY, Wen ML, Zhuang SS, Hua J, He XP. Application of endoscopic ultrasonography for detecting esophageal lesions based on convolutional neural network. World J Gastroenterol 2022; 28(22): 2457-2467
URL: https://www.wjgnet.com/1007-9327/full/v28/i22/2457.htm
DOI: https://dx.doi.org/10.3748/wjg.v28.i22.2457

Liu GS, Huang PY, Wen ML, Zhuang SS, Hua J, He XP. Application of endoscopic ultrasonography for detecting esophageal lesions based on convolutional neural network. World J Gastroenterol 2022; 28(22): 2457-2467 [PMID: 35979257 DOI: 10.3748/wjg.v28.i22.2457]

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