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

Table 4 Artificial intelligence applications in gastroenterology: Prognosis

Ref.	Parameters employed	AI classifier	Sizes of the training/validation sets	Outcomes	Performance
Yang et al[97]	Laboratory results, immunomarkers, clinicopathological parameters	SVM	319/164 patients	Distant metastasis of oesophageal squamous cell carcinoma following surgery	69.5-80.11,6, 44.7-67.23,6, 81.6-97.74,6
Sato et al[98]	Laboratory results, clinicopathological parameters, tumor characteristics	ANN	395 patients (training:validation:test = 53:27:20)	1-year and 5-year survival of patients with esophageal cancer following surgery	0.883-0.8842,7, 78.1-80.73,7, 84.7-86.54,7
Zhou et al[99]	Laboratory results, clinicopathological parameters, tumor characteristics	Several	2012 patients (training:validation = 8:2)	Recurrence of gastric cancer following surgery	0.790-0.9622,5, 0.771-0.7952,6
Peng et al[100]	Meteorological data	ANN	901 patients	Variations of onset and relapse of IBDs	----
Hardalaç et al[101]	Clinicopathological parameters, treatment data	ANN	129 patients (training:validation:test = 80:10:10)	Prediction of mucosal remission for CD patients treated with azathioprine	58.1-79.11,6, 0.527-0.8832,6
Takayama et al[102]	Clinicopathological parameters, treatment data	ANN	54/36 patients	Prediction of the need for operation for UC patients treated with cytoapheresis	963,6, 974,6
Lyles et al[103]	Laboratory results, clinicopathological parameters	CART	884 patients	Prediction of in-hospital mortality of upper GIB in cirrhotic patients	----
Grossi et al[104]	Laboratory results, clinicopathological parameters	ANN	807 patients	30-d mortality of patients with non-variceal upper GIB	81.2-89.01,6, 0.872,6, 81.5-93.33,6, 80.9-84.74,6
Rotondano et al[105]	Laboratory results, clinicopathological parameters	ANN	2380 patients	30-d mortality of patients with non-variceal upper GIB	96.81,6, 0.952,6, 83.83,6, 97.54,6
Shi et al[106]	CT radiomics	Several	124/35 patients	Prediction of the presence of RAS and BRAF mutations in CRC	ANN: 871,5, 711,6, 0.90-0.952,5, 0.792,6
Kang et al[107]	Laboratory results, immunomarkers, clinicopathological parameters, tumor characteristics	LASSO	221/95 patients	Prediction of lymph node metastasis status in operated patients for T1 CRC	0.7952,5, 0.7652,6

¹Accuracy (%).

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

³Sensitivity (%).

⁴Specificity (%).

⁵Training.

⁶Internal validation.

⁷External validation/testing. ANN: Artificial neural network; CART: Classification and regression tree; CD: Chron’s disease; CRC: Colorectal cancer; CT: Computed tomography; GIB: Gastrointestinal bleeding; IBD: Inflammatory bowel disease; LASSO: Least absolute shrinkage and selection operator; SVM: Support vector machine; UC: Ulcerative colitis.