Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology

Table 8 Artificial intelligence applications in hepatology: Prognosis

Ref.	Parameters employed	AI classifier	Sizes of the training/validation sets	Outcomes	Performance
Hong et al[142]	Laboratory results, clinicopathological parameters	ANN	197 HBV patients (training:validation = 4:1)	Development of esophageal varices in HBV cirrhosis	87.821,6, 93.753,6, 71.704,6
Dong et al[143]	Laboratory results, clinicopathological parameters	RF	238/1097	Identification of esophageal varices	0.842,5, 0.822,7
				Classification of esophageal varices requiring treatment	0.742,5, 0.752,7
Ho et al[144]	Laboratory results, clinicopathological parameters, surgery parameters	ANN, DT	427, 354, and 297 patients for 1-, 3-, and 5-year survival (training:validation = 8:2)	1-, 3-, and 5-year disease-free survival	ANN: 0.963-0.9892,5, 93.5-96.33,5, 91.6-97.94,5, 0.774-0.8642,6, 70.0-78.73,6, 54.2-92.74,6
				Following surgical resection
					DT: 0.675-0.8252,5, 19.6-94.83,5, 45.8-97.94,5, 0.561-0.7182,6, 0-88.53,6, 37.5-96.44,6
Shi et al[145]	Laboratory results, clinicopathological parameters, tumor characteristics	ANN	22926 patients	5-year survival following surgical resection	96.571,6, 0.8852,6, 97.431,7, 0.8712,7, 74.233,7,
Shi et al[146]	Laboratory results, clinicopathological parameters, surgery parameters	ANN	22926 hepatectomies	In-hospital mortality following surgical resection	97.281,6, 0.842,6, 95.931,7, 0.822,7, 78.403,7, 94.574,7
Chiu et al[147]	Laboratory results, clinicopathological parameters, tumor characteristics	ANN	434, 341, and 264 patients for 1-, 3-, and 5-year survival, (training:validation = 8:2)	1-, 3-, and 5-year overall survival, following surgical resection	98.5-99.51,5, 0.980-0.9932,5, 99.7-1003,5, 96.2-99.24,5, 72.1-85.11,6, 0.798-0.8752,6, 71.4-88.63,6, 50.0-82.14,6
Qiao et al[148]	Laboratory results, clinicopathological parameters, tumor characteristics	ANN	362/1816/1047 patients	Survival following surgical resection	0.8552,5, 80.003,5, 73.404,5, 0.8322,6, 78.673,6, 75.704,6, 0.8292,7, 77.423,7, 78.084,7
Liu et al[149]	Laboratory results, data from immunochemistry of peripheral blood mononuclear cells, tumor characteristics	GB survival classifier	136/566/1057	Risk of HCC-related death	0.8442,5, 0.8272,6, 0.8062,7
Zhong et al[150]	ALBI/CTP stage	ANN	319 / 617 / 1247	Survival of patients treated with chemoembolization and sorafenib	ALBI-based: 0.7162,7, 0.8232,7
					CTP-based: 0.7792,7, 0.6932,7
Divya and Radha[152]	Laboratory results, clinicopathological parameters, tumor characteristics	APO, SVM, RF	152 patients	Recurrence following RFA	95.51,6, 95.13,6, 95.84,6
Yamashita et al[153]	Hematoxylin and eosin-stained WSI	CNN	299 / 536/1987 WSIs	Recurrence following Surgical Resection	0.7242,6, 0.6832,7
Liang et al[154]	Laboratory results, clinicopathological parameters	SVM	83 patients	Recurrence following RFA	73-821,6, 0.60-0.692,6, 77-863,6, 73-824,6
Eaton et al[155]	Laboratory results, clinicopathological parameters	GB-based	509/278 patients with primary sclerosing cholangitis	Classify risk of primary sclerosing cholangitis-related complications	0.962,6, 0.902,7
Andres et al[156]	Laboratory results, clinicopathological parameters, donor characteristics	PSSP system	2769 patients	Survival following transplantation for primary sclerosing cholangitis	----
Rodriguez-Luna et al[157]	Genotyping data from microsatellite mutations/deletions	ANN	19 transplated patients	Post-transplant HCC recurrence	89.51,6
Lau et al[158]	Laboratory results, clinicopathological parameters, donor characteristics	ANN, RF	90/90 transplants	Graft failure/primary nonfunction	ANN: 0.734-0.8352,6
					RF: 0.787-0.8182,6
				3-mo graft failure	ANN: 0.5592,6, R6: 0.7152,6
Briceño et al[160]	Laboratory results, clinicopathological parameters, surgical parameters, donor characteristics	ANN	1003 liver transplants	3-mo graft failure	0.806-0.8212,6

¹Accuracy (%).

²Area under the receiver operating curve or c-index.

³Sensitivity (%).

⁴Specificity (%).

⁵Training.

⁶Internal validation.

⁷External validation/testing. ALBI: Albumin-bilirubin; ANN: Artificial neural network; APO: Artificial plant optimization; CNN: Convolutional neural network; CTP: Child–Turcotte–Pugh; DT: Decision tree; GB: Gradient boosting; HBV: Hepatitis B; HCC: Hepatocellular carcinoma; PSSP: Patient-specific survival prediction; RF: Random forest; RFA: Radiofrequency ablation; SVM: Support vector machine; WSI: Whole-slide image.