Risk Assessment Of Alzheimer's Disease Based On Empirical Bayesian Estimation

Alzheimer's disease is a common primary degenerative brain disease of the nervous system.The present study of Alzheimer's disease is only limited to the medical field.However,due to the lack of strict definition of the symptoms of Alzheimer's disease in the field of international medicine,it is difficult for patients to be found in the early phase of the disease,so the treatment measures will always be delayed.The significance and innovation of this article is to determine whether an individual is suffering from Alzheimer's disease by establishing an Alzheimer's risk assessment model,thus screening the individual with Alzheimer's disease or early Alzheimer's phase and reducing the risk of Alzheimer's disease by giving pre-intervention therapy.First of all,this article analyzed the factors associated with Alzheimer's disease,and found that the effects of various factors on Alzheimer's disease could be quantified by the detection of the apparent diffusion coefficient(ADC)in the associated part of the brain.What is more,We also found that the four parts of the brain,like white matter in the frontal lobe,the pressure of the corpus callosum,the white matter of the temporal lobe,and the white matter of the parietal lobe,have been found to have a more significant effect on the individuals with Alzheimer's disease compared to other parts in human's brain through the related medical literature.Therefore,this paper will get the apparent diffusion coefficient(ADC)value of these four interested regions by Function 2 software obtained from the The Openfmri site,and analyzed the correlation between the associated ADC values of these four parts and the age and sex.Due to the intersection of the normal individuals and the sick individuals in the ADC interval of these four regions,we can not fully judge whether the value is abnormal or normal in the case of the ADC value of the region of interest in the brain of an individual.Therefore,we need to establish the Alzheimer's risk assessment model based on the existing data.Obviously,the problem links to binomial distribution's parameter estimation problem.By introducing and comparing several feasible methods of estimating binomial distribution parameters(such as maximum likelihood estimation,95% confidence interval upper limit method,Bias estimation method,classical Bias estimation method,etc.),it is found that the estimation accuracy of HBM method is the best method.Therefore,the parameter estimation results obtained by HBM method are used.The risk assessment model can be established by integrating the ADC abnormal rate in four regions of interest.Therefore,if there is a new individual to be tested,the risk of the individual can be roughly judged by detecting the ADC value of each area of interest in the brain,and whether it should be given first time treatment.