Design And Implementation Of Intelligent Health Management System For Specific Population

In recent years,with the continuous development of science and technology,computers have penetrated into various fields of research,the most popular is the medical field.Intelligent health management system integrates medical and computer related technologies.Implementing individualized health assessment for the population,formulating individualized health plan,and implementing health intervention reasonably and effectively in a scientific way.To prevent and treat the occurrence and development of chronic diseases and common diseases,to minimize the risk of sudden diseases,so as to improve the quality of life of patients,reduce the use of medical expenses,and achieve comprehensive health management for specific populations.Blood pressure is an important characteristic index of human health.And blood pressure is closely related to our daily habits and physical condition.Early management of people's health and effective prevention and prediction of blood pressure can reduce the occurrence of cardiovascular and cerebrovascular diseases.In this paper,an improved M-GM(1,1)multi-dimensional grey model is proposed to solve the problem of large error in the process of data prediction by studying the algorithm of blood pressure prediction.M-GM(1,1)model predicts future blood pressure by processing and analyzing the blood pressure data of individuals for several consecutive days,thus realizing the short-term prediction function for people's health.The experimental results show that M-GM(1,1)model can effectively predict the short-term blood pressure,and the accuracy is improved compared with other models.This paper describes the algorithms used in blood pressure and disease prediction in recent years,and implements an intelligent health management system for efficient management and monitoring of health design of specific populations.Specific groups refer to students aged 18-25,elderly people over 65 or people with obvious occupational characteristics such as miners.Intelligent health management system is mainly used to monitor people's health,at the same time to impart targeted health knowledge,health management early warning and health trend tracking.In addition,an integrated intelligent health management service system will be established for the population by means of statistics,detection,early warning and other means starting from data collection.Then the modeling process of grey prediction model is described in detail,and the grey GM(1,1)model is optimized,and M-GM(1,1)is proposed.The experimental results show that the accuracy of M-GM(1,1)for blood pressure prediction is improved.Subsequently,the system needs analysis and development,completed all the functions of the intelligent health management system,M-GM(1,1)is applied to the intelligent health management system,can use the user's recent blood pressure to predict the follow-up blood pressure,so as to achieve the monitoring of physical health.Finally,the function and performance test of the system ensures the perfection of the system's performance and function,and provides the basis for correct operation for field use.