Open access
Aug 2026
Prediction of mortality risk in patients with peripheral artery disease using interpretable machine learning
An interpretable random forest model for predicting postoperative mortality in PAD is established and validates the nonlinear prognostic significance of NLR and demonstrates how explainable ML can complement traditional statistics for individualized risk assessment.
Yi-Fei Li, Qiang Zhang, Wen-Xin Zhao et al.
· Frontiers in Cardiovascular... · 0 citations