{"title":"Future Generation Computing in M-Health","authors":"","doi":"10.4018/978-1-7998-4537-9.ch008","DOIUrl":null,"url":null,"abstract":"The implementation of healthcare-related big data in m-health has constantly been considered as the most prevalent technological breakthrough of the modern era. Indeed, the use of healthcare-related big data in m-health is a pivotal and substantially challenging task and is still not chiefly considered by the researchers. This is predominantly indispensable owing to the perpetual cascading of structured and unstructured datasets being elicited abundantly from multifold m-health applications within the purview of diverse healthcare systems. Perhaps, there are many innovative paradigms, which, if synergistically used in the domain of m-health, can generate the next level of computing in this purview. This chapter will render the relevance of big data from the point of view of m-health as well as the existing and future attributions of different machine and deep learning techniques in the pursuit of m-health.","PeriodicalId":198416,"journal":{"name":"Cloud-Based M-Health Systems for Vein Image Enhancement and Feature Extraction","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cloud-Based M-Health Systems for Vein Image Enhancement and Feature Extraction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-7998-4537-9.ch008","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 implementation of healthcare-related big data in m-health has constantly been considered as the most prevalent technological breakthrough of the modern era. Indeed, the use of healthcare-related big data in m-health is a pivotal and substantially challenging task and is still not chiefly considered by the researchers. This is predominantly indispensable owing to the perpetual cascading of structured and unstructured datasets being elicited abundantly from multifold m-health applications within the purview of diverse healthcare systems. Perhaps, there are many innovative paradigms, which, if synergistically used in the domain of m-health, can generate the next level of computing in this purview. This chapter will render the relevance of big data from the point of view of m-health as well as the existing and future attributions of different machine and deep learning techniques in the pursuit of m-health.
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
移动医疗中的下一代计算
在移动医疗中实施与医疗相关的大数据一直被认为是现代最流行的技术突破。的确,在移动医疗中使用与医疗保健相关的大数据是一项关键且极具挑战性的任务,研究人员仍然没有主要考虑到这一点。由于结构化和非结构化数据集的永久级联,从不同医疗保健系统范围内的多重移动医疗应用程序中大量提取,这在很大程度上是必不可少的。也许,有许多创新的范例,如果在移动医疗领域协同使用,可以在这一范围内产生更高水平的计算。本章将从移动医疗的角度来呈现大数据的相关性,以及在追求移动医疗过程中不同机器和深度学习技术的现有和未来属性。
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
Approaches for M-Health Environment Results and Discussions of Palm-Dorsa-Veins-Based Systems in the Cloud IoT-Based M-Health Environment The Panoramic Views of Cloud IoT-Based M-Health Biometrics A Glimpse of Hardware Design Approaches Future Generation Computing in M-Health
×
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