Role of artificial intelligence in the characterization of indeterminate pancreatic head mass and its usefulness in preoperative diagnosis

Table 2 Studies on differentiation of indeterminate lesions using artificial intelligence algorithms on computed tomography images

No.	Ref.	Number of patients	Primary objective	Sub-type of AI used	Outcome
1	Qureshi et al[36], 2022	108	Identification of PDAC	ML	Accuracy: 86%
2	Ebrahimian et al[121], 2022	103	Differentiation of benign vs malignant pancreatic lesions	RF	AUC: 0.94
3	Chakraborty et al[59], 2018	103	High risk vs low risk IPMN	RF, SVM	AUC: 0.81
4	Polk et al[60], 2020	29	High risk vs low risk IPMN	LR	AUC: 0.90
5	Ikeda et al[122], 1997	71	PDAC vs pancreatitis	NN	AUC: 0.916
6	Chen et al[58], 2021	100	SCN vs MCN	LASSO and RFE_Linear SVC	AUC: 0.932
7	Yang et al[57], 2019	53	SCN vs MCN	LASSO	AUC: 0.66
8	Yang et al[123], 2022	63	SCN vs MCN	MMRF-ResNet	AUC: 0.98
9	Ren et al[124], 2020	112	PDAC vs pancreatic adenosquamous carcinoma	RF	AUC: 0.98
10	Xie et al[125], 2021	226	MCN vs ASCN	RF	AUC: 0.734
11	Ziegelmayer et al[126], 2020	86	AIP vs PDAC	CNN, ML	AUC: 0.90
12	Li et al[62], 2022	97	Focal-type AIP vs PDAC	LASSO regression	AUC: 0.97
13	Gao et al[127], 2021	170	MCN vs SCN	mRMR + LASSO	AUC: 0.91
14	Dmitriev et al[53], 2017	134	Classification of pancreatic cyst	RF, CNN	Accuracy: 83.6%
15	Li et al[54], 2019	206	Classification of pancreatic cysts	DNN (Dense-Net)	Accuracy: 72.8%
16	Wei et al[56], 2019	260	SCN vs other cystic neoplasms	ML	AUC: 0.767

AI: Artificial intelligence; AIP: Autoimmune pancreatitis; ASCN: Atypical serous cystic neoplasm; AUC: Area under the curve; CNN: Convolutional neural network; DNN; Deep neural network; IPMN: Intraductal papillary mucinous neoplasm; LASSO: Least absolute shrinkage and selection operator; LR: Logistic regression; MCN: Mucinous cystic neoplasm; ML: Machine learning; PDAC: Pancreatic ductal adenocarcinoma; RFE: Recursive feature elimination; RF: Random forest; SCN: Serous cystic neoplasm; SVM: Support vector machine; NN: Neural network; mRMR: Minimum redundancy maximum relevance; SVC: Support vector classifier; MMRF: Multi-channel-multiclassifier-random forest.