Design And Implementation Of Mobile Web Health Big Data Platform Based On HTML5 And Node.js

With the rapid development of information technology in modern society,people's life has become more and more inseparable from the Internet.Especially in the era of mobile Internet,wireless network,like 3G,4G,WIFI,becomes popular rapidly,the number of mobile APP also has sprung up and emerged in endlessly,surfing the Internet by smartphones or tablet computer become the mainstream of the Internet world.Diseases such as chronic diseases,which are represented by high blood pressure and cancer,threaten human health much.As a result of the rapid change of the medical equipment,hospital and medical institutions have accumulated a large amount of raw health data.We can use machine learning or data mining technology to find the value of the health big data,in order to provide human disease prediction service.The purpose of this thesis is to design and implement a mobile web health big data platform based on HTML5 and Node.js.People can make their own assessment of the risk of high blood pressure or cancer,anytime and anywhere via the platform.The research of this thesis mainly focuses on the design and implementation of the health big data platform.Firstly,the thesis studies the big data technologies of Logistic regression,MLP neural network and BP algorithm,as well as the mobile Web front-end and server side development technology,in order to realize the platform.Secondly,the thesis analyzes the demand of the mobile Web health big data platform,including the functional demands of chronic disease prediction and cancer screening,as well as mobile Web software platform stability,fitment,flexibility and other non-functional demands.Thirdly,according to the proposed demands,the thesis designed a layered system architecture based on B/S architecture model,and the process of the two functions of chronic disease prediction and cancer screening was designed.Fourthly,the thesis realized both the front-end and the back-end of the mobile Web software platform by using components and modules.A high blood pressure risk model and a cancer screening model is established and applied in the software platform.Last but not least,the software platform is tested and repaired and improved during testing.In this thesis,a high blood pressure risk model based on Logistic regression and Harvard Cancer Risk Index Formula and a cancer risk model based on MLP are established.The models are applied in a mobile Web health big data platform,which is implemented by modular components.The platform is in good condition,and excellent user experience is provided.