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

doi:10.3748/wjg.v28.i22.2457

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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 4 Comparative sensitivity, specificity, and accuracy results of classification branch of object detection network and classification network alone

	SENS	SPEC	ACC
Object detection classify	0.5839	0.8404	0.7861
Classification network alone	0.7400	0.9070	0.8733

SENS: Sensitivity; SPEC: Specificity; ACC: Accuracy.

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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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