S. Prasad, S. Sangavi, A. Deepa, F. Sairabanu, R. Ragasudha
{"title":"Diabetic data analysis in big data with predictive method","authors":"S. Prasad, S. Sangavi, A. Deepa, F. Sairabanu, R. Ragasudha","doi":"10.1109/ICAMMAET.2017.8186738","DOIUrl":null,"url":null,"abstract":"Diabetes mellitus is one of the major non-communicable diseases which have great impact on human life today. Due to the life style and work culture changes in the 21st century, India houses 62 million diabetes in it. By applying computational analytics on clinical big data, the massive amount of data generated in the healthcare systems, will be used to create medical intelligence which will drive medical prediction and forecasting. Developing medical intelligence out of the clinical data available will create healthcare system to be patient-centered and will reduce medical cost and hospital readmission too. Big Data Analytics improves health care system through the reduction run time and the optimal cost. It ability to make the banking and healthcare decision based on the communication made by system. This system values the predictive investigation of algorithm in Hadoop/Map Reduce environment to predict and classify the type of Diabetic Mellitus, Type-1 diabetes does not produce the insulin in our body. In 10% of people with diabetes have this form of the disease. In Type-2 diabetes does not use insulin properly in our body. Generally around the 24th week — many women establish gestational diabetes while the pregnancy is increasing.","PeriodicalId":425974,"journal":{"name":"2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAMMAET.2017.8186738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
Diabetes mellitus is one of the major non-communicable diseases which have great impact on human life today. Due to the life style and work culture changes in the 21st century, India houses 62 million diabetes in it. By applying computational analytics on clinical big data, the massive amount of data generated in the healthcare systems, will be used to create medical intelligence which will drive medical prediction and forecasting. Developing medical intelligence out of the clinical data available will create healthcare system to be patient-centered and will reduce medical cost and hospital readmission too. Big Data Analytics improves health care system through the reduction run time and the optimal cost. It ability to make the banking and healthcare decision based on the communication made by system. This system values the predictive investigation of algorithm in Hadoop/Map Reduce environment to predict and classify the type of Diabetic Mellitus, Type-1 diabetes does not produce the insulin in our body. In 10% of people with diabetes have this form of the disease. In Type-2 diabetes does not use insulin properly in our body. Generally around the 24th week — many women establish gestational diabetes while the pregnancy is increasing.