Research And Implementation Of Hypertension Incidence Probability Prediction System Based On Association Rules

Big data and intelligent idea are changing our real lifestyle.The concept of green-life is slowly beening accepted.People are paying more attention to their own health.However,many people fail to understand their physical condition correctly and in a timely manner.Which results in missing the right time of treatment,and the tragedy that leads to the treatment of the disease becomes more common.Among them,the sedetection and early treatment” is one of the problems actively studied by the scientific research community.Both large and small hospitals have begun to use the electronic medical record system to manage patient information,which clearly implies various factors that influence the disease.If we can use data mining frontier technology to identify various potential factors from these raw materials and their impact on the incidence of hypertension,it will be a milestone in our diagnosis and prevention of hypertension.Data mining technology is one of the most effective and practical means for mining hidden information behind data at this stage.It aims to find out the connections between data or information,using these connections as the initial mining results,and using a screening strategy to screen out rules that are useful for decision makers.The Fp-growth algorithm is a representative data mining algorithm,which performs tree compression storage on data,which improves the efficiency of frequent item set search.This paper uses Fp-growth as a frequent item set search algorithm to mine hypertension data and realize the prediction system of hypertension incidence probability.Through the Fp-growth algorithm,the frequent itemsets of hypertension factors are extracted from the electronic medical records and the corresponding rules are found.These rules serve as a knowledge base in the design of a system for predicting the probability of developing hypertension.The paper implemetes a system which predicts the probability of hypertension incidence by incorporating Fp-growth algorithm.In this system,by entering a profile,the users can automatically generate prediction results and suggestions.In Addition,this system enables patients to be more timely aware of the impact of their lifestyle on their blood pressure,thereby correcting bad lifestyles and achieving early prevention of timely treatment.