Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis

doi:10.3748/wjg.v26.i34.5156

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Sep 14, 2020 (publication date) through Apr 24, 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. Sep 14, 2020; 26(34): 5156-5168
Published online Sep 14, 2020. doi: 10.3748/wjg.v26.i34.5156

Table 3 Performance of the binary classifiers

	Plain scan	Arterial phase	Venous phase	χ² value	P value
Accuracy	0.954747	0.957580	0.951549	0.346	0.841
Specificity	0.982710	0.975695	0.978692	0.149	0.928
Sensitivity	0.915758	0.940808	0.922756	0.914	0.633

Citation: Ma H, Liu ZX, Zhang JJ, Wu FT, Xu CF, Shen Z, Yu CH, Li YM. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis. World J Gastroenterol 2020; 26(34): 5156-5168
URL: https://www.wjgnet.com/1007-9327/full/v26/i34/5156.htm
DOI: https://dx.doi.org/10.3748/wjg.v26.i34.5156