中国针灸2026，Vol.46Issue(5)：678-686,9.DOI:10.13703/j.0255-2930.20250510-k0001
基于可解释性机器学习算法构建针刺干预腰椎间盘突出症预后评估模型
Construction of a prognostic assessment model of acupuncture intervention for lumbar disc herniation based on interpretable machine learning algorithms
摘要
Abstract
Objective To construct and validate a prognostic assessment model of acupuncture intervention for lumbar disc herniation(LDH),and analyze the key factors of acupuncture efficacy,so as to provide the decision support for clinical individualized treatment.Methods Clinical data of 478 LDH patients were retrospectively analyzed.The least absolute shrinkage and selection operator(LASSO)regression was used to select predictive variables,and 8 machine learning prediction models were constructed,including decision tree,random forest,extreme gradient boosting,support vector machine,multilayer perceptron,logistic regression,light gradient boosting machine,and K-nearest neighbor.The performance of each model was evaluated through five-fold cross-validation.SHapley additive exPlanations(SHAP)method was employed to analyze model interpretability,and an online interactive application based on Shiny was developed.Results LASSO regression selected 15 predictive variables;the support vector machine performed the best in five-fold cross-validation,with an average area under the receiver operating characteristic curve(AUC)of 0.862 and an average Brier score of 0.157.Decision curve analysis indicated a good clinical application value for this model.SHAP analysis showed that the combined therapies of acupuncture with Fu's acupuncture,warm needling,electroacupuncture and acupuncture delivered once daily were associated with favorable prognosis;and the higher body mass indexes(BMI),engagement in heavy physical labor,and the use of glucocorticoids and hyperosmotic dehydration agents,as well as the disc herniation of different segments and spinal canal stenosis were associated with unfavorable prognosis.Conclusion The interpretable machine learning-based prognostic assessment model of acupuncture intervention for LDH demonstrates a good predictive performance,providing evidence for clinical individualized treatment.However,more external validations are required for its optimization.关键词
腰椎间盘突出症/针刺/机器学习/临床预测模型Key words
lumbar disc herniation/acupuncture/machine learning/clinical prediction model引用本文复制引用
王喆,宁乙锞,崔华峰,刘兴雨,丁瑞欣,姜国梁,盛春月,韩晶..基于可解释性机器学习算法构建针刺干预腰椎间盘突出症预后评估模型[J].中国针灸,2026,46(5):678-686,9.基金项目
山东省中医药疗效机理重点实验室项目:PKL2024C23 （）
泰山学者工程专项经费资助项目:tsqn202312376 （）
济南市中医针灸临床医学研究中心项目:济科技[2023]1号 （）
