Construct validation of machine learning models for predicting surgical site infection risk following ankle fracture surgery

The findings of this study demonstrate that modern ML methods offer high predictive accuracy for SSI risk, with the GBM model outperforming the traditional logistic regression model. This study provides strong evidence for the clinical application of ML-based risk assessment, suggesting that integrating preoperative risk factors with ML techniques can enable more precise, individualized treatment strategies for the prevention and management of SSI.