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 23, 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 5 Performance of the ternary classifiers

Dataset	Plain scan	Arterial phase	Venous phase	χ² value	P value
Accuracy	0.820568	0.790633	0.788076	1.074	0.585
Specificity	0.985721	0.984770	0.990305	0.577	0.749
Sensitivity (cancer at the tail/body of pancreas)	0.520122	0.411098	0.360272	1.841	0.398
Sensitivity (cancer at the head/neck of pancreas)	0.462148	0.852390	0.728743	16.651	< 0.001

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