Health Monitoring System Using Integration of Cloud and Data Mining Techniques

Author Name(s): *Asadi Srinivasulu, G.M.Chanakya, E Sandhya, A.Ramprakash Reddy, K.Lakshmi Prasanna
Author Email: srinu.asadi@gmail.com

Abstract

The data in healthcare is expected to increase in coming years as there are different kinds of health data like EHR (Electronic Health Records), genomic, that are processed with big data processing. Although many technologies are used for big processing with health care records, which uses predictive analysis however which is not sufficient for all kind of health records. Big Data Mining (BDM) methods, for example, proposal framework, order, grouping, affiliation, relapse and so on are broadly utilized as a part of human services field as of late to help enhance the quality, productivity and in addition bringing down the cost of creating social insurance frameworks. A coordination of cloud and Data mining Techniques is presented that gives a compelling approach to diminish the time, and cost of programming advancement and also state-of-the-art administrations. The data is collected from the patient and an immediate prescription is given based on the data. Further this data is been stored in the cloud data storage and is delivered to the end users. In this project we plan to predict and detect disease by mining patient’s health data like diabetes detection by using K-NN algorithm, high blood pressure prediction and heart disease detection by using K-Means algorithm.

Keywords

K-NN algorithm, K-Means algorithm, Clustering, Classification, Google Cloud Messaging, Android.

Introduction

Information mining procedures have been generally utilized as a part of medicinal services field because of its proficient systematic approach for recognizing significant data in wellbeing information, accessibility of therapeutic answer for the patients at lower cost, location of reasons for sicknesses and distinguishing proof of restorative treatment strategies. The “pay for utilize” estimating model, on-request registering are utilized. The result of the framework is to give advantages to medicinal services association by gathering system. The Issues that is inescapable while building up this framework. The primary test is to get quality and significant medicinal information the second test is to information investigation is a testing work and the third test is the means by which to give an instrument which can break the outskirt of the patient and clinic administration. Information mining is a procedure of extricating the extensive measure of data from the huge informational collections by utilizing the calculations and methods that are drawn from the field of insights, machine learning and information base administration frameworks.

Conclusion

Cloud computing and Data Mining has extraordinarily changed the method for creating programming from multiple points of view, it gives a quick, minimal effort, sheltered and simple approach to outline new programming. In our work, we outlined and incompletely executed a far reaching social insurance framework sickness forecast and identification. The framework is composed and created by the unpretentious, simple to convey, powerful, minimal effort and constant standards. For the following phase of research, first thing is to execute the entire framework, at that point do inside and out recreations to approve the framework execution, specifically, reenact different situations to affirm its versatility with a specific end goal to apply our framework to genuine condition. A few calculations are under thought to enhance their execution, for example, utilizing K*-implies, UK intends to supplant k-implies. We likewise plan to extend our framework to iOS stage later on.

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