中国药房2025，Vol.36Issue(21)：2723-2726,4.DOI:10.6039/j.issn.1001-0408.2025.21.18
气象因素驱动的布地奈德高用药日预测集成学习模型的构建与比较
Meteorological factor-driven prediction of high-use days of budesonide:construction and comparison of ensemble learning models
摘要
Abstract
OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors,thereby providing reference for hospital pharmacy management.METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected.High-use days were defined as the 75th percentile of outpatient budesonide usage,and a corresponding dataset was established.The prediction task was formulated as a classification problem,and three ensemble learning models were developed:Random Forest,Extreme Gradient Boosting(XGBoost),and Histogram-based Gradient Boosting Classifier.Model performance was evaluated using accuracy,precision,recall,F1-score,and log-loss.Model interpretability was analyzed using Shapley Additive Explanations(SHAP).RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance(accuracy=0.75,F1-score=0.48),followed by XGBoost(accuracy=0.74,F1-score=0.43)and Random Forest(accuracy=0.72,F1-score=0.22).SHAP results suggested that the prediction results of the last two models have the highest correction.CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide,with the Histogram-based Gradient Boosting Classifier demonstrating the best predictive performance.Low temperature,high humidity,and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.关键词
布地奈德/气象因素/集成学习/可解释性人工智能Key words
budesonide/meteorological factors/ensemble learning/explainable artificial intelligence分类
药学引用本文复制引用
陈祺焘,周悦,张晓俊,倪璟雯,孙国强,高分飞,夏丽珍,李梓豪..气象因素驱动的布地奈德高用药日预测集成学习模型的构建与比较[J].中国药房,2025,36(21):2723-2726,4.基金项目
国家中医药管理局项目(No.国中医药人教函[2022]75号) （No.国中医药人教函[2022]75号）
2025年度福建省自然科学基金项目(No.2025J011566) （No.2025J011566）
福建中医药大学校管课题临床专项(No.XB2024075) （No.XB2024075）
