Traditional Chinese Medicine Diagnosis Of Stroke Based On Data Mining Study On The Rule Of Drug Use

Stroke is also called "stroke" or "cerebrovascular accident." It is an acute cerebrovascular disease.According to research,stroke is currently the leading cause of death in our country.At the same time,stroke is also the first disease syndrome that causes adult residues in our country.According to different people’s physiques,Chinese medicine can adopt the method of dialectical treatment,according to the characteristics of different physiques,formulate prescriptions and use drugs,and treat according to the symptoms and signs.In this context,in order to further explore the treatment of stroke and the rule of stroke medication,the paper constructs a stroke medication rule analysis model,including the CC bi-clustering model,random forest and applicability rules,and gradually explores the brain The law of medical medicine for stroke,to realize the excavation and summary of the law of medication.The main research contents of this paper are as follows:In this context,in order to further explore the dialectical treatment of stroke and study the medication law of stroke,this paper constructs the analysis model of medication law of stroke,including CC double clustering model,random forest and applicability rules,to gradually explore the medication law of stroke in traditional Chinese medicine,and realize the mining and summary of medication law.The main contents of this paper are as follows(1)Through the analysis of the research model of the law of traditional Chinese medicine for stroke,we found the limitations of the traditional Chinese medicine law research and the insufficiency of the research on the law of stroke medicine,and proposed a new model of research on the law of traditional Chinese medicine for stroke.(2)Construction and simulation application of the key component mining model of stroke.Analyzed the limitations of the current research on the treatment of stroke with traditional Chinese medicine,and proposed a new mining model based on the CC biclustering model.Through the introduction of punishment strategies,an optimized CC biclustering model was built,and the key components for the treatment of stroke were discovered.(3)The construction and simulation application of the mining model of stroke differentiation and medication rule.In view of the characteristics of TCM syndrome differentiation and treatment,through further mining of the key component matrix,a random forest model was built to screen the top 10 core drugs that have the greatest impact on the treatment of stroke.In combination with the rules of applicability,the corresponding pathogenesis of the core drugs in different dose ranges is discovered to achieve the purpose of syndrome differentiation.In this paper,through machine learning,we build a double clustering model,random forest model,and combined with the applicability rules,applied to the mining of TCM medication rules of stroke,and realized the research of TCM medication rules of stroke.It plays an effective assistant decision-making role in clinical medication.