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
Table 1 Layer 4 (full-feature model): Internal validation performance comparison across 14 algorithms
| Algorithm | AUC | AUC_95CI | AUPRC | Brier | ABscore | Accuracy | Sensitivity | Specificity | F1 | PPV | NPV | Opt_Threshold |
| LightGBM | 0.7507 | 0.6872-0.8157 | 0.5592 | 0.1856 | 1.0 | 0.7191 | 0.7907 | 0.6851 | 0.6445 | 0.544 | 0.8732 | 0.3144 |
| RotF | 0.7454 | 0.6783-0.8091 | 0.5333 | 0.1875 | 0.9583 | 0.7266 | 0.7326 | 0.7238 | 0.6332 | 0.5575 | 0.8506 | 0.3459 |
| GBDT | 0.7367 | 0.6723-0.7967 | 0.5439 | 0.1876 | 0.9113 | 0.6704 | 0.7791 | 0.6188 | 0.6036 | 0.4926 | 0.855 | 0.2922 |
| RF | 0.7252 | 0.6620-0.7862 | 0.5171 | 0.1935 | 0.8075 | 0.6779 | 0.8023 | 0.6188 | 0.6161 | 0.5 | 0.8682 | 0.3333 |
| SVM | 0.7222 | 0.6581-0.7879 | 0.5327 | 0.1938 | 0.7892 | 0.6779 | 0.7093 | 0.663 | 0.5865 | 0.5 | 0.8276 | 0.294 |
| AdaBoost | 0.7172 | 0.6472-0.7794 | 0.509 | 0.1976 | 0.7349 | 0.6479 | 0.8023 | 0.5746 | 0.5948 | 0.4726 | 0.8595 | 0.3209 |
| ExtraTrees | 0.7169 | 0.6519-0.7812 | 0.5125 | 0.1988 | 0.7248 | 0.6966 | 0.686 | 0.7017 | 0.593 | 0.5221 | 0.8247 | 0.3487 |
| KNN | 0.7162 | 0.6553-0.7778 | 0.4889 | 0.1977 | 0.7287 | 0.6517 | 0.7326 | 0.6133 | 0.5753 | 0.4737 | 0.8284 | 0.4286 |
| MLP | 0.7132 | 0.6436-0.7778 | 0.522 | 0.2539 | 0.3016 | 0.6667 | 0.7442 | 0.6298 | 0.5899 | 0.4885 | 0.8382 | 0.0523 |
| DT | 0.7096 | 0.6463-0.7688 | 0.4685 | 0.1951 | 0.7131 | 0.6667 | 0.7442 | 0.6298 | 0.5899 | 0.4885 | 0.8382 | 0.4217 |
| XGBoost | 0.6956 | 0.6276-0.7603 | 0.4896 | 0.1971 | 0.6243 | 0.633 | 0.7791 | 0.5635 | 0.5776 | 0.4589 | 0.843 | 0.2972 |
| GAM | 0.6848 | 0.6158-0.7573 | 0.4956 | 0.1997 | 0.5487 | 0.6554 | 0.6395 | 0.663 | 0.5446 | 0.4741 | 0.7947 | 0.3507 |
| LR | 0.6689 | 0.5988-0.7375 | 0.4832 | 0.2022 | 0.446 | 0.6667 | 0.5581 | 0.7182 | 0.5189 | 0.4848 | 0.7738 | 0.3677 |
| NB | 0.656 | 0.5881-0.7276 | 0.4897 | 0.2376 | 0.1198 | 0.6592 | 0.593 | 0.6906 | 0.5285 | 0.4766 | 0.7812 | 0.3976 |
- 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