Copyright
©The Author(s) 2025.
World J Gastroenterol. Jul 21, 2025; 31(27): 108200
Published online Jul 21, 2025. doi: 10.3748/wjg.v31.i27.108200
Published online Jul 21, 2025. doi: 10.3748/wjg.v31.i27.108200
Figure 3 Performance of machine learning models to predict hepatic steatosis.
Receiver operating characteristic curves of the four performing machine learning models. RF: Random Forest; LR: Logistic regression; SVM: Support Vector Machine; ROC: Receiver operating characteristic; AUC: Area under the curve.
- Citation: Tian Y, Zhou HY, Liu ML, Ruan Y, Yan ZX, Hu XH, Du J. Machine learning-based identification of biochemical markers to predict hepatic steatosis in patients at high metabolic risk. World J Gastroenterol 2025; 31(27): 108200
- URL: https://www.wjgnet.com/1007-9327/full/v31/i27/108200.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i27.108200