Design And Implementation Of Medical Big Data Analysis And Prediction System Based On Regression Model

With the rapid economic growth,the country continues to increase investment in the medical field,and the scale of hospitals has expanded rapidly.However,the service level and management level of medical institutions have not been correspondingly improved with the expansion of the hospital scale,resulting in maladjustment of medical service supply and various "difficult to see a doctor".How to improve the level of medical services and management has become a very critical challenge in the medical field.The rapid expansion of the hospital’s scale has resulted in the medical data generated by the hospital being expanded and accumulated at an unprecedented speed.Existing hospital institutions only use the traditional hospital information management system to store and query these massive medical data..This not only wastes huge resources of the hospital for unreasonable data storage,but also fails to dig deep into the hidden data value because of the inability to analyze and use these medical data in time.For the purpose of transforming medical data into intuitive graphics,digging into the value of data,storing medical big data reasonably,improving the service and management level of medical institutions,this paper designs and develops a medical big data analysis and prediction system based on regression model.This system summarizes the medical data of the medical industry,analyzes the development trend of various medical data indicators in the form of a line chart,and analyzes the proportion of the historical value of each medical data indicator in the form of a radar chart.Through the monitoring and analysis of these indicators,the transaction volume,health,and development speed of medical institutions are pictured,so as to provide a reference function for managers to formulate specific strategies to improve the level of medical services.The medical data prediction function is mainly aimed at the prediction of the number of inpatients in each hospital.The number of inpatients is affected by many factors.The system uses a support vector regression model that simultaneously models multiple input indicators to predict the number of inpatients in the hospital.Medical institution managers can make advance preparations for medical consumables and adjust the number of hospital beds based on the prediction of the number of inpatients,which can provide a reference for the hospital to plan ahead for scientific and effective management.The implementation of this system adopts B / S architecture,the development tools use Eclipse tools,the development language is Java,the JDK version is 1.8.0,the development framework of this system selects the Spring framework,the system architecture is based on the MVC design pattern,and the database uses Oracle and HBase databases.In the design and development of medical big data analysis and prediction system in this article,I participated in various stages of system feasibility analysis,system requirements survey,system summary design,system detailed design and implementation,and system testing.It is mainly responsible for the design and implementation of the homepage data display module,map monitoring module,data analysis module,number prediction module,system demand analysis,establishment of medical data index system,installation of Oracle and HBase database,construction of Hadoop ecological environment and preparation of related test cases.The system performs functional testing and performance testing.At present,the system has been put into use,with comprehensive data analysis,accurate data prediction,and good feedback from the target users of the system.