
An intelligent online evaluation system for mediolateral episiotomy was developed using machine learning models trained on maternal physiological data. Among six models tested, the support vector machine (SVM) demonstrated the highest predictive accuracy. SHAP analysis identified key risk factors, including perineal elasticity and BMI. The system provides real-time risk assessment, enhancing clinical decision-making and improving maternal care during labor.
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