Classification Of Score Of Quality Of The Femoral Neck Surgery Based On Two Methods Of Data Mining

The orthopedists care about the Harris score(score of quality of the femoral neck surgery).As the patient cases accumulate,we hope find the impact factors about the Harris score and predict the Harris score of one new patient on the base of the impact factors of this patient.Bayesian network classifier based on probability theory and graph theory has a good classification function and has been widely used in the fields of medical diagnosis,statistic analysis and artificial intelligence.Decision tree is a simple and widely used classifier based on the theory of information gain.From the perspective of data mining,First of all,This paper give an account of basic components and development tendency of data mining,then,provides detailed information on decision tree and bayesian network classifier.Finally,To solve the problem of classification of Harris score,the paper create the excellent decision tree classifier and bayesian network classifier of score of quality of the femoral neck surgery,using the Optimized tree L-C4.5 algorithm and the bayesian network classifier.on these basis,the paper find the impact factors about the Harris score: BMI,Type of Garden,having diabetes or not,parallel side screw or not,three-legged Structure or not,classification of fracture.