Big Data, Analyzing and Modelling: New Ways of Health Improvement and Regional Aspects

V. Kopytko, Lyubov Shevchuk, L. Yankovska, Zhanna Semchuk
{"title":"Big Data, Analyzing and Modelling: New Ways of Health Improvement and Regional Aspects","authors":"V. Kopytko, Lyubov Shevchuk, L. Yankovska, Zhanna Semchuk","doi":"10.22178/POS.37-2","DOIUrl":null,"url":null,"abstract":"The field of health improvement and life prolonging develops poorly, despite all the advances in medicine, chemistry and genetic engineering. Among the main problems is the difficulty of using new scientific achievements in other industries due to the rapid development of specialized knowledge, the problem of returning costs for the creation of really effective and the problem of aging population in developed countries. There are problems with data for this methods usage with privacy and security on different levels with regional peculiarities. Effective timing of work on health at the personal level can result as a result of increased time and productivity. But it's difficult for people to allocate their intellectual resources for that, so you have to connect artificial intelligence and machine learning. Big Data model with methods and analysis techniques on different levels for health improvement was suggested. The importance of the level of social networks and its regional aspects for the analysis of health improvement data was identified. Big data processing results implementation and levels of interaction with human with request for changes model was proposed. It consists from two levels of interaction with humans by level of quick reaction and discussion with smart personal assistance. Regional aspects from possible AI implementation in undeveloped countries were analyzed on example of personal level big data for health usage.","PeriodicalId":410291,"journal":{"name":"ERN: Analytical Models (Topic)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Analytical Models (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22178/POS.37-2","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 field of health improvement and life prolonging develops poorly, despite all the advances in medicine, chemistry and genetic engineering. Among the main problems is the difficulty of using new scientific achievements in other industries due to the rapid development of specialized knowledge, the problem of returning costs for the creation of really effective and the problem of aging population in developed countries. There are problems with data for this methods usage with privacy and security on different levels with regional peculiarities. Effective timing of work on health at the personal level can result as a result of increased time and productivity. But it's difficult for people to allocate their intellectual resources for that, so you have to connect artificial intelligence and machine learning. Big Data model with methods and analysis techniques on different levels for health improvement was suggested. The importance of the level of social networks and its regional aspects for the analysis of health improvement data was identified. Big data processing results implementation and levels of interaction with human with request for changes model was proposed. It consists from two levels of interaction with humans by level of quick reaction and discussion with smart personal assistance. Regional aspects from possible AI implementation in undeveloped countries were analyzed on example of personal level big data for health usage.
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
大数据、分析与建模:健康改善新途径与区域层面
尽管医学、化学和基因工程都取得了进步,但改善健康和延长生命的领域发展缓慢。其中主要的问题是,由于专业知识的快速发展,新的科学成果难以应用于其他行业,真正有效的创造的回报成本问题,以及发达国家的人口老龄化问题。该方法使用的数据存在隐私和安全问题,在不同的层次上具有区域特性。由于时间和生产力的增加,可以在个人层面上有效地安排健康工作的时间。但人们很难分配他们的智力资源,所以你必须把人工智能和机器学习联系起来。提出了基于不同层次的健康改善方法和分析技术的大数据模型。确定了社会网络水平及其区域方面对健康改善数据分析的重要性。提出了基于变更请求的大数据处理结果实现和人机交互层次模型。它包括两个层次的互动与人类的快速反应和讨论与智能个人协助的水平。以卫生用途的个人层面大数据为例,分析了不发达国家可能实施人工智能的区域方面。
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
Comparing City Size Distributions: Population vs. Economic Activity The Road to Integration: Post-Migration Experience and Migrant Housing Behavior in Singapore Regional Housing Market Conditions in Spain Evidence-based COVID-19 Response in Ethiopia: A quasi-Experimental Study on Social Distancing Industrial Structure and a Tradeoff between Productivity and Resilience
×
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