基于Python开源数据科学生态的中医肺胀病中药处方探析与膏方调理策略探索OA
Exploration of Traditional Chinese Medicine Prescriptions and Herbal Paste Conditioning Strategies for Lung Distension Disease Based on Python's Open-Source Data Science Ecosystem
基于 Python 开源数据科学生态,挖掘中医肺胀病中药处方的用药规律,分析其核心证候,并据此探索稳定期膏方调理策略,以应对临床面临的高再入院率挑战.方法:收集与整理 2022 年 1 月——2024 年 12 月安溪县中医院开具的中药处方共计415 张.利用 Python 的 Pandas、NumPy 等库进行数据清洗与预处理,应用 Apriori 算法进行关联规则分析以挖掘高频药物组合,采用聚类分析对处方进行分组,并统计不同证候下的药物使用特征.结果:共涉及中药 173 味,高频药物包括山茱萸(67.23%)、茯苓(56.39%)、生甘草(54.22%)、沉香(49.64%)等.证候分布以肺肾气虚证(28.19%)、痰湿蕴肺证(18.07%)及肺肾两虚证(17.83%)为主.关联规则分析显示,"山茱萸-炒山药-熟地黄-茯苓"为核心药物组合(支持度 37.11%),该组合源于六味地黄丸与四君子汤,体现了"补肾健脾、益肺化痰"的核心治法.聚类分析进一步验证了以补肾健脾为核心、兼顾温化寒痰、清热化痰的处方族群分类.结论:本研究通过数据驱动的方法,揭示了肺胀病治疗中以补肾健脾为本、化痰利湿为标的用药规律.基于此规律,创新性提出以核心药物组合为基础,构建用于肺胀病稳定期长期调理的中药膏方方案.该策略旨在实现从"被动住院救治"向"主动门诊管理"的模式转变,为降低疾病复发率、优化中医药慢病管理实践提供了循证依据与可行路径.
This study leverages Python's open-source data science ecosystem to mine the medication patterns of Traditional Chinese Medicine(TCM)prescriptions for lung distension disease,analyze its core syndromes,and accordingly explore herbal paste conditioning strategies for the stable phase,so as to address the clinical challenge of high readmission rates.Method:A total of 415 TCM prescriptions diagnosed and prescribed Anxi Hospital of Traditional Chinese Medicine from January 2022,to December,2024 were collected and organized.Python libraries such as Pandas and NumPy were used for data cleaning and preprocessing.The Apriori algorithm was applied for association rule analysis to mine high-frequency herb combinations,and cluster analysis was employed to group the prescriptions and statistically characterize herb usage under different syndromes.Result:The study involved 173 distinct Chinese herbs.High-frequency herbs included Cornus officinalis(67.23%),Poria cocos(56.39%),raw Glycyrrhiza uralensis(54.22%),and Aquilaria sinensis(49.64%).Syndrome distribution was primarily lung-kidney qi deficiency syndrome(28.19%),phlegm-dampness obstructing the lung syndrome(18.07%),and lung-kidney deficiency syndrome(17.83%).Association rule analysis revealed the core herb combination"Cornus officinalis-stir-fried Dioscorea opposita-Rehmannia glutinosa-Poria cocos"(support 37.11%),which derives from the classic formulas Liuwei Dihuang Wan and Sijunzi Tang,embodying the core treatment principle of"tonifying the kidney and spleen,benefiting the lung and resolving phlegm".Cluster analysis further validated the classification of prescription clusters centered on tonifying kidney and spleen,while also addressing warming and resolving cold phlegm and clearing heat and resolving phlegm.Conclusion:This data-driven study reveals the medication pattern for lung distension disease,which is fundamentally based on tonifying the kidney and spleen,with the secondary aim of resolving phlegm and dampness.Based on this pattern,we innovatively propose constructing a TCM herbal paste formulation based on the core herb combination for the long-term conditioning of lung distension disease during its stable phase.This strategy aims to facilitate a paradigm shift from"passive inpatient treatment"to"active outpatient management,"providing evidence-based justification and a feasible pathway for reducing disease recurrence rates and optimizing TCM chronic disease management practices.
谢梅萍;许晓斌;苏忆明;陈泽宇;陈东海
安溪县中医院 福建 泉州 362400安溪县中医院 福建 泉州 362400安溪县中医院 福建 泉州 362400安溪县中医院 福建 泉州 362400安溪县中医院 福建 泉州 362400
Python数据挖掘肺胀病用药规律膏方
PythonData miningLung distension diseaseMedication patternHerbal paste
《中外医学研究》 2026 (10)
34-40,7
泉州市中医临床重点专科建设项目(泉卫中医函[2024]269号)
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