Artificial intelligence in medical imaging of the liver

Table 1 Clinical application of artificial intelligence

n	Task	Type	Accuracy	Sensitivity	Specificity	Ref.
1	Detecting fatty liver disease and making risk stratification	Deep learning based on US	100%	100%	100%	[42]
2	Detecting and distinguishing different focal liver lesions	Deep learning based on US	97.2%	98%	95.7%	[43]
3	Evaluating liver steatosis	Deep learning based on US	96.3%	100%	88.2%	[49]
4	Evaluating chronic liver disease	Machine learning algorithm based on SWE	87.3%	93.5%	81.2%	[12]
5	Discriminating liver tumors	DCCA-MKL framework based on US	90.41%	93.56%	86.89%	[50]
6	Predicting treatment response	Machine learning algorithm based on MRI	78%	62.5%	82.1%	[58]

DCCA-MKL: Deep canonical correlation analysis-multiple kernel learning; MRI: Magnetic resonance imaging; US: Ultrasound.