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©The Author(s) 2025.
World J Gastrointest Surg. Apr 27, 2025; 17(4): 103696
Published online Apr 27, 2025. doi: 10.4240/wjgs.v17.i4.103696
Published online Apr 27, 2025. doi: 10.4240/wjgs.v17.i4.103696
Figure 6 Gradient-boosting tree model for the risk of postoperative death in patients who underwent abdominal surgery.
The independent influencing factors used in the process of establishing the model were derived from the multivariate logistic regression analysis. APTT: Activated partial thromboplastin time; AST: Aspartate aminotransferase; TBIL: Total bilirubin; WBC: White blood cell.
- Citation: Yuan JH, Jin YM, Xiang JY, Li SS, Zhong YX, Zhang SL, Zhao B. Machine learning-based prediction of postoperative mortality risk after abdominal surgery. World J Gastrointest Surg 2025; 17(4): 103696
- URL: https://www.wjgnet.com/1948-9366/full/v17/i4/103696.htm
- DOI: https://dx.doi.org/10.4240/wjgs.v17.i4.103696