中图分类号 R969.3；TP8 文献标志码 A 文章编号 00-0408(2025)-399-06

    DOI 0.6039/j.issn.00-0408.2025..20

    ABSTRACT OBJECTIVE To construct three-class (insufficient， normal， excessive) and two-class (insufficient， normal) models for predicting plasma concentration of valproic acid(VPA)，and compare the performance of these two models，with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024(a total of 695 sets of data). In this study，predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation，and the performance of the models was evaluated using three indexes： accuracy，F1 score，and the area under the working characteristic curve of the subject (AUC). RESULTS XGBoost feature importance scores revealed that in the three-class model ......