Research On Early Prediction And Prevention Model Of Clinical Disease Complicated By Alzheimer’s Disease Based On Machine Learning

As a common dementia disease,Alzheimer’s disease(AD)has become a research hotspot in the medical field because of its high de gree of harm and the incurable characteristics.Existing studies have shown that the early stage of mild cognitive impairment(MCI)of the disease is also closely related to other chronic senile diseases.Therefore,early prevention,diagnosis and treatment of AD can effectively slow down and prevent the formation of AD.This thesis first uses the combination of filtering and wrapping methods to select features,and use the selected feature subsets to establish an individual prediction model of MCI and improve the model.The accuracy,specificity and sensitivity of the model are used as the standard to measure the pros and cons of the model.Comparing the effects of the model before and after the improvement,it is found that the model prediction accuracy rate has been increased from 77.3%before the improvement to 81.6%,which has realized the optimization of the individual prediction model and improved the accuracy of the individual prediction.Secondly,take the parameters of the improved model as important influence coefficients to establish a system dynamics model based on MCI conversion.In addition,the model also adopts the method of progressively combining machine learning and system dynamics,analyzes the correlation between the detection indicators through association rules,and introduces it as a driving mechanism into the system dynamics model to construct a differential equation of migration dynamics.Control the dynamic transformation process of each stage in the model,The system dynamics simulation experiment is used to realize the dynamic prediction of the development of healthy elderly population to AD.On the basis of the above analysis,the migration of the population at each stage is analyzed,and the prevalence of eac h stage is obtained,so as to realize realtime monitoring of the development of the disease.Finally,a three-level prevention mechanism was established based on the MCI conversion model.The primary prevention and control mainly provides early prevention of senile diseases for the normal population,and achieves the preventive effect on AD by reducing the probability of the normal population suffering from senile diseases;The secondary prevention and control is to treat people suffering from senile disea ses,thereby inhibiting the further development of the disease,thereby reducing the risk of concurrent MCI and AD in the population;The tertiary prevention and control is to intervene in the early MCI stage of AD to slow down the development of MCI disease and prolong the development cycle of AD.According to the results of the simulation,the effect of disease prevention and control is as follows: first-level prevention,second-level prevention,third-level prevention and treatment.Therefore,it can be concluded that the earlier intervention measures are adopted,the better the prevention and treatment effect of AD.