Extended definition of medical big data

Fadia Shah, Jianping Li, Y. Shah, F. Shah
{"title":"Extended definition of medical big data","authors":"Fadia Shah, Jianping Li, Y. Shah, F. Shah","doi":"10.1109/ICSESS.2017.8342967","DOIUrl":null,"url":null,"abstract":"The human life is always experiencing problems related to health. The survival is difficult if not treated well. For a better recovery, health problems are solved by treatment plans and medications; which are by health care professional called specialists, doctors or medical practitioners. Whatever these professionals recommend, it is well maintained in the form of reports. The collection of all this record makes Medical Big Data (MBD). Based upon the medical problem, this MBD includes medical history and prescription reports, test reports, X-Ray, CT Scan, and some other types of medical diagnosis. Traditional systems are now improved after the enhancements in telecommunication modes and innovation of smart devices with latest 5G technology has a huge contribution in every field of science. Regarding health care systems, in developed countries, E-Health and Telemedicine systems being developed to improve the quality of treatment. Such systems have many enhanced features like data management, reliable diagnoses; among them a distinct aspect is load reduction for the patient about data availability and management. Since MBD is increasing for every patient as the time passes and the patient consults again and again. Many schemes with efficient models are proposed to make this MBD available over the network by compression and network management tools. This exponential expansion of MBD has unmitigated the domains of MBD generating sources. In this paper, MBD collection, sources are discussed which ensure directly or indirectly how some domains are responsible to increase MBD more than normal ways.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"78 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2017.8342967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The human life is always experiencing problems related to health. The survival is difficult if not treated well. For a better recovery, health problems are solved by treatment plans and medications; which are by health care professional called specialists, doctors or medical practitioners. Whatever these professionals recommend, it is well maintained in the form of reports. The collection of all this record makes Medical Big Data (MBD). Based upon the medical problem, this MBD includes medical history and prescription reports, test reports, X-Ray, CT Scan, and some other types of medical diagnosis. Traditional systems are now improved after the enhancements in telecommunication modes and innovation of smart devices with latest 5G technology has a huge contribution in every field of science. Regarding health care systems, in developed countries, E-Health and Telemedicine systems being developed to improve the quality of treatment. Such systems have many enhanced features like data management, reliable diagnoses; among them a distinct aspect is load reduction for the patient about data availability and management. Since MBD is increasing for every patient as the time passes and the patient consults again and again. Many schemes with efficient models are proposed to make this MBD available over the network by compression and network management tools. This exponential expansion of MBD has unmitigated the domains of MBD generating sources. In this paper, MBD collection, sources are discussed which ensure directly or indirectly how some domains are responsible to increase MBD more than normal ways.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
医疗大数据扩展定义
人的一生总是会遇到与健康有关的问题。如果治疗不好,生存是困难的。为了更好地康复,健康问题是通过治疗计划和药物来解决的;这是由被称为专家、医生或医疗从业人员的卫生保健专业人员进行的。无论这些专业人员推荐什么,它都以报告的形式得到了很好的维护。所有这些记录的集合构成了医疗大数据(MBD)。基于医疗问题,本MBD包括病史和处方报告、检查报告、x光片、CT扫描和一些其他类型的医疗诊断。在电信模式的增强之后,传统系统得到了改进,智能设备的创新与最新的5G技术在每个科学领域都有巨大的贡献。关于保健系统,在发达国家,正在开发电子保健和远程医疗系统,以提高治疗质量。这样的系统有许多增强的功能,如数据管理、可靠的诊断;其中一个独特的方面是减轻患者在数据可用性和管理方面的负担。因为随着时间的推移,MBD对每个病人来说都在增加,病人一次又一次地咨询。为了通过压缩和网络管理工具使MBD在网络上可用,提出了许多具有有效模型的方案。这种MBD的指数级扩展扩大了MBD产生源的范围。本文讨论了MBD集合的来源,这些来源直接或间接地确保了某些域如何比正常方式更负责增加MBD。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Critical analysis of feature model evolution A key technology survey and summary of dynamic network visualization Soft decision strategy design for signal demodulation in IEEE 802.11 protocol suite based wireless communication process A prediction method based on improved ridge regression SuperedgeRank algorithm and its application for core technology identification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1