Research On The Collection And Analysis Of Body Data Based On Big Data

In recent years,the degree of informationization of medical institutions has continued to increase,and the amount of various types of medical and health information has increased dramatically.Due to the uniqueness of large amount of data and outstanding diversity of medical health data,the types of data to be collected and processed have also become more complex and diverse.Traditional medical data processing techniques have gradually failed to meet current needs,How to collect and analyze medical and health big data and dig out potential value from it is still a question worth studying.As a common medical big data,physical data can better reflect the characteristics of medical big data than other data.Aiming at the physical data,this paper researches the existing data collection methods and data analysis methods,and designs a body data collection and analysis system based on big data.The system realizes the collection,storage,analysis,management and visualization of body data.Aiming at the characteristics of physical data,this paper studies the current status of the development of big data collection at home and abroad,analyzes the advantages and disadvantages of mainstream big data collection products,designs and formulates the structure of the body data collection cluster,and divides each component module of the cluster.The configuration and implementation of each component module are described in detail.Aiming at the existing association classification algorithms in data mining,this paper improves the classic association classification algorithm by introducing full confidence,and proposes an improved association classification algorithm.This algorithm is different from the traditional association classification algorithm based on the support-confidence model.It uses a full-confidence discrimination mechanism,which greatly reduces the number of rules generated.The algorithm also improves the process of the new instance prediction stage,so that It is more suitable for mining and analyzing body data.The comparison experiment of the algorithm using standard data sets verifies the algorithm's performance in terms of computational efficiency and prediction accuracy.Finally,based on the above research,a body data collection and analysis system was designed and implemented.Various functions of the system were tested,and simulation experiments were performed on the improved algorithm,using real body data sets for analysis,and comparing with the existing common algorithms,verifying the superiority of the improved algorithm in body data mining.