Prediction of Chronic Diseases in Elderly Based on Boltzmann Machine

To explore more and better for the elderly health assessment method, based on the understanding of other evaluation methods, this paper considers using artificial neutral network to the Bayesian method in the prior probability to obtain optimized effect, increases the applicability of a posteriori probability, in order to realize the judgement of various factors on the impact caused by disease of aging. This paper proposes a chronic disease prediction and management model for the elderly based on the Boltzmann machine from the perspective for ecological civilization, it has a clear understanding of the methods of health assessment and disease diagnosis for the elderly, a detailed introduction of domestic and foreign research, and an understanding of the assessment process and advantages and disadvantages of each method. It is proposed to combine the Boltzmann machine method to evaluate the health of the elderly (for a certain disease), predict its feasibility and verify. According to the experimental simulation, the advantages of the new method, the need for improvement and whether it can be extended to other similar diseases can be comprehensively evaluated.