Research And Application Of The Disease Duxiliary Diagnosis Method

At present,almost all doctors diagnose disease according to their experience,the results were heavily dependent on the doctor's ability.For some Difficult miscellaneous diseases must depend on experts,but the number of experts is limited,which often leads to delays in the treatment.In addition to some remote areas,which limited medical resources,doctors experience level is limited,the rate of misdiagnosis is very high.So it is very important to use the technology of data mining to combine the medical informat:ion in the present medical system and develop the auxiliary diagnosis system.This paper analyzes the existing medical data in the database,according to the characteristics of the medical data in the database,the original medical data was preprocessed,and the features were reduced dimensionally according to the characteristics of the data used in the analysis.In order to improve the generalization ability of the disease diagnosis model,this paper introduces the Adaboost integration algorithm based on the C4.5 algorithm.V-AdaBoost algorithm and L-AdaBoost algorithm are proposed to solve the problem in medical field based on AdaBoost.Then V-AdaBoost algorithm and L-AdaBoost algorithm are used to construct the disease diagnosis model.Experiments show that both V-AdaBoost algorithms and L-AdaBoost have better performance than AdaBoost.Finally,based on V-AdaBoost algorithm and L-AdaBoost algorithm,the disease diagnosis system is realized.The system can predict the probability of patients,provide guidance for the doctor's diagnosis,improve the diagnostic efficiency of doctors,which shows the system has certain application value.