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 4 Precision-recall curves for the four-layer models.
A: Layer 1 precision-recall curves (demographics); B: Layer 2 precision-recall curves (demographics + inflammation); C: Layer 3 precision-recall curves (demographics + lipid); D: Layer 4 precision-recall curves (all features). PPV: Positive predictive value; RotF: Rotation Forest; GBDT: Gradient Boosting Decision Tree; MLP: Multi-Layer Perceptron; RF: Random Forest; KNN: K-Nearest Neighbors; GAM: Generalized Additive Model; SVM: Support Vector Machine; DT: Decision Tree; LR: Logistic regression; NB: Naive Bayes.
- 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