ERBB2 and gastric cancer: Researchers have constructed machine learning models using texture or deep features extracted from preoperative contrast-enhanced CT imaging to predict several biomarkers in patients with gastric cancer: PD-L1 positive expression (area under the curve [AUC] 0.77‐0.78) [16, 17], HER2 overexpression (AUC 0.72‐0.91) [18, 19], and MSI-H status (AUC 0.76‐0.91) [20-22].