©The Author(s) 2025.
World J Gastroenterol. Dec 21, 2025; 31(47): 114370
Published online Dec 21, 2025. doi: 10.3748/wjg.v31.i47.114370
Published online Dec 21, 2025. doi: 10.3748/wjg.v31.i47.114370
Figure 3 Establishing a diagnostic nomogram for early postoperative complications.
A: Nomogram for the diagnosis of early postoperative complications; B: Calibration curve for prediction accuracy; C: Receiver operating characteristic curves of four indexes in the cohort; D: The receiver operating characteristic curve of the combination of four indexes; E: Decision curve analysis for the nomogram. LnSII: Log-transformed systemic immune inflammatory index; IV PL: Partial lobectomy of segment IV; AUC: Area under the curve; MELD: Model for end-stage liver disease.
- Citation: Wang D, Zhang JY, Xie Y, Zhang KN, Jiang WT. Interpretable machine learning model for early complication prediction after split liver transplantation. World J Gastroenterol 2025; 31(47): 114370
- URL: https://www.wjgnet.com/1007-9327/full/v31/i47/114370.htm
- DOI: https://dx.doi.org/10.3748/wjg.v31.i47.114370