Copyright: ©Author(s) 2026.
World J Gastroenterol. Dec 14, 2026; 32(46): 121708
Published online Dec 14, 2026. doi: 10.3748/wjg.121708
Published online Dec 14, 2026. doi: 10.3748/wjg.121708
Figure 1 Flow chart of the study design.
CRC: Colorectal cancer; KNN: K-Nearest Neighbors; SVM: Support Vector Machine; MLP: Multi-Layer Perceptron; GBDT: Gradient Boosting Decision Tree; AUC: Area under the curve; AUROC: Area under the receiver operating characteristic; PPV: Positive predictive value; NPV: Negative predictive value; SHAP: SHapley Additive exPlanations; LCR: Lymphocyte-to-C-reactive protein ratio; BMI: Body mass index; ApoB/ApoA1: Apolipoprotein B-to-apolipoprotein A1 ratio.
- Citation: Du YY, Liu YM, Fang RY, Zheng HG. Inflammation-lipid metabolism biomarker-based machine learning models for predicting postoperative pulmonary metastasis in colorectal cancer. World J Gastroenterol 2026; 32(46): 121708
- URL: https://www.wjgnet.com/1007-9327/full/v32/i46/121708.htm
- DOI: https://dx.doi.org/10.3748/wjg.121708