©The Author(s) 2025.
World J Gastroenterol. Oct 7, 2025; 31(37): 111038
Published online Oct 7, 2025. doi: 10.3748/wjg.v31.i37.111038
Published online Oct 7, 2025. doi: 10.3748/wjg.v31.i37.111038
Figure 1 Feature selection process.
A: Recursive feature elimination (RFE) algorithm results; B: Least absolute shrinkage and selection operator (LASSO) regression feature selection; C: Intersection of features selected by RFE, minimum redundancy maximum relevance, and LASSO. RFE: Recursive feature elimination; LASSO: Least absolute shrinkage and selection operator; mRMR: Minimum redundancy maximum relevance.
- Citation: Zhu DL, Tulahong A, Liu C, Aierken A, Tan W, Ruze R, Yuan ZD, Yin L, Jiang TM, Lin RY, Shao YM, Aji T. Identification of key factors and explainability analysis for surgical decision-making in hepatic alveolar echinococcosis assisted by machine learning. World J Gastroenterol 2025; 31(37): 111038
- URL: https://www.wjgnet.com/1007-9327/full/v31/i37/111038.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i37.111038