M. Babar, Muhammad Jehanzeb, Masitah Ghazali, D. Jawawi, Falak Sher, S. Ghayyur
{"title":"医疗大数据现状调查及智能数据诊断框架构想","authors":"M. Babar, Muhammad Jehanzeb, Masitah Ghazali, D. Jawawi, Falak Sher, S. Ghayyur","doi":"10.1109/COMPCOMM.2016.7924654","DOIUrl":null,"url":null,"abstract":"Healthcare is one of the core areas in medical domain. In healthcare the data exist in various forms like respiration data, blood pressure readings, prescriptions and others. The data may help in decision-making for different initiatives in order to provide better healthcare services. However, in order to make this possible there is a need to diagnose the data in a professional way. Currently, there is a lack of a system or way which may help in decision-making in big data analysis in the form of phases. In this research, a framework has been proposed to diagnose the healthcare data for efficient data analysis.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Big data survey in healthcare and a proposal for intelligent data diagnosis framework\",\"authors\":\"M. Babar, Muhammad Jehanzeb, Masitah Ghazali, D. Jawawi, Falak Sher, S. Ghayyur\",\"doi\":\"10.1109/COMPCOMM.2016.7924654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Healthcare is one of the core areas in medical domain. In healthcare the data exist in various forms like respiration data, blood pressure readings, prescriptions and others. The data may help in decision-making for different initiatives in order to provide better healthcare services. However, in order to make this possible there is a need to diagnose the data in a professional way. Currently, there is a lack of a system or way which may help in decision-making in big data analysis in the form of phases. In this research, a framework has been proposed to diagnose the healthcare data for efficient data analysis.\",\"PeriodicalId\":210833,\"journal\":{\"name\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPCOMM.2016.7924654\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPCOMM.2016.7924654","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big data survey in healthcare and a proposal for intelligent data diagnosis framework
Healthcare is one of the core areas in medical domain. In healthcare the data exist in various forms like respiration data, blood pressure readings, prescriptions and others. The data may help in decision-making for different initiatives in order to provide better healthcare services. However, in order to make this possible there is a need to diagnose the data in a professional way. Currently, there is a lack of a system or way which may help in decision-making in big data analysis in the form of phases. In this research, a framework has been proposed to diagnose the healthcare data for efficient data analysis.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
