Artificial intelligence in medical imaging of the liver

doi:10.3748/wjg.v25.i6.672

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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. Feb 14, 2019; 25(6): 672-682
Published online Feb 14, 2019. doi: 10.3748/wjg.v25.i6.672

Table 3 Diffuse liver disease staging

n	Type	AUCs	Ref.
1	Deep learning based on MRI	F4: 0.84; ≥ F3: 0.84; ≥ F2: 0.85	[45]
2	Deep learning based on CT	F4: 0.73; ≥ F3: 0.76; ≥ F2: 0.74	[46]
3	Deep learning based on SWE	F4: 0.97; ≥ F3: 0.98; ≥ F2: 0.85	[32]

AUC: Area under the receiver operating characteristic curve; MRI: Magnetic resonance imaging; CT: Computed tomography; SWE: Shear wave elastography.

Citation: Zhou LQ, Wang JY, Yu SY, Wu GG, Wei Q, Deng YB, Wu XL, Cui XW, Dietrich CF. Artificial intelligence in medical imaging of the liver. World J Gastroenterol 2019; 25(6): 672-682
URL: https://www.wjgnet.com/1007-9327/full/v25/i6/672.htm
DOI: https://dx.doi.org/10.3748/wjg.v25.i6.672