Study On The Algorithm Model Of Acupuncture And Moxibustion For The Treatment Of Knee Osteoarthritis

Research Objective:The subject is based on knee osteoarthritis,an acupuncture-predominant disease,and its knowledge base is constructed and quantified by obtaining clinical and literature research and acupuncture and moxibustion data for patients with knee osteoarthritis.The subject was obtained by taking knee osteoarthritis,an acupuncture-predominant disease,and obtaining knee osteoarthritis patients.The knowledge base was constructed and quantitatively encoded by obtaining clinical and literature research and acupuncture and moxibustion data of patients with knee osteoarthritis.Based on the"46 symptom quantization code",Optimize the elements of the syndrome,Using machine learning technology and association rule algorithm to construct acupuncture and moxibustion treatment of knee osteoarthritis with"symptom-syndromes-acupoint"intelligent syndrome differentiation algorithm model.To provide a computerized method for dialectical differentiation of acupuncture and moxibustion for the realization of digitized and intelligent diagnosis and treatment of knee osteoarthritis.Research Method:1.The data of four diagnoses and acupoints of 93 patients with clinical knee osteoarthritis were collected,based on 46 symptom quantization code,quantitative coding of clinical four-diagnosis information and acupoint data,optimization of syndrome elements,to obtain the elements of KOA disease syndrome,combined with syndrome dialectic system to quantify the syndrome elements,research on the Model of Dialectical Algorithm Using Machine Learning Technology;2.The 207 pieces of acupuncture treatment KOA clinical research literature were classified into syndrome type,meridian and acupoint sorting,combined with clinically collected syndrome types,meridians and acupoints to establish syndrome type-acupoint correspondence database,and Apriori association rule algorithm was used to mine syndrome type-Frequent itemsets of acupoints,summarizing the internal correlation rules of syndrome-type acupoints,and giving an optimization plan for KOA syndrome-group recommendation;3.After the syndrome-type syndrome differentiation algorithm model dialectical calculation can obtain the syndromes,analysis of Association Rules of Combination Type-Acupoint Apriori Algorithm.An algorithmic model for acupuncture and moxibustion for the treatment of"symptoms-types-acupoints"of knee osteoarthritis was obtained.Research Result:1.Based on the"46 symptom quantification code"and"syndrome differentiation system",this study proposes to establish 24 syndrome elements of knee osteoarthritis disease:disease location syndrome elements:heart,bladder,gallbladder,spleen,kidney,bones,Liver,large intestine,stomach,clean room;disease nature syndrome elements:wind,yin deficiency,heat,yang deficiency,dryness,consumption,cold,blood stasis,dampness,qi deficiency,accumulation,loss of qi,qi stagnation,collateral resistance;2.The clinical patient four syndrome data symptom data is quantified and coded according to the symptom-symptom element weighting table,and the syndrome value of all the patients of the syndrome type is attributed to the sum of the weights of a certain syndrome element/（the number of symptoms of the syndrome type）=the initial weight of the syndrome element,thus determining:the default weight of all syndrome elements of the syndrome=the initial weight of the syndrome element_i^{P（ki）（28）?XSi??}?_i^{??XR y?}?^?Sxi is the weight of Mx to Ni;Rxy is the frequency of the symptom Mx of the syndrome type Ky.After machine learning and calculation,and the weights are adjusted several times,the default weights of the syndrome elements of each syndrome type are obtained,and the syndrome model of syndrome of knee osteoarthritis-syndrome type is obtained.3.According to the association analysis of Apriori algorithm combined with the acupuncture points and meridian syndrome differentiation theory,get KOA symptoms-syndromes-acupoint intelligent group recommendation:the recommended group of cold and dampness syndrome is:Neixiyan,Liangqiu,Waixiyan,Yanglingquan,Zusanli;liver and kidney deficiency syndrome recommended group points:Zusanli,Yinlingquan,Yingu,Ququan;damp heat and stasis syndrome recommended group points:Neixiyan,Yinlingquan,Heding,Zusanli;recommended stagnation of qi stagnation and blood stasis syndrome:Neixiyan,Yinlingquan,Ashi,and Ququan;recommended groups of qi and blood deficiency syndrome are:Zusanli,Waixiyan,Liangqiu,Neixiyan,Xuehai;Research Conclusion:In this study,93 patients with KOA patients were collected for clinical diagnosis and acupoint data collection.Using factor analysis combined with principal component analysis to extract common factors.The basis of"46 symptom quantification code"and"syndrome differentiation system"In combination with the etiology and pathogenesis theory of knee osteoarthritis,the following conclusions are drawn:1.KOA-24 syndrome elements:disease location syndrome elements:heart,bladder,gallbladder,spleen,kidney,bones,Liver,large intestine,stomach,clean room;disease nature syndrome elements:wind,yin deficiency,heat,yang deficiency,dryness,consumption,cold,blood stasis,dampness,qi deficiency,accumulation,loss of qi,qi stagnation,collateral resistance;The weights of the syndrome elements are adjusted several times,and the syndrome-type syndrome differentiation algorithm model is obtained through the syndrome calculation.2.Using Apriori association rule algorithm to explore the relationship between syndrome type and acupuncture points,and give the recommendation of the optimized group point scheme of knee osteoarthritis syndrome type-acupoint,completed the research on the intelligent syndrome differentiation and selection algorithm model of knee osteoarthritis.3.The initial construction of the intelligent syndrome differentiation and selection algorithm model of knee osteoarthritis,and the need for greater data volume for verification in the later stage,further and more in-depth research to improve.