Big data in health and disease: re-processing information for discovery and validation

R. Yeung, E. Capobianco
{"title":"Big data in health and disease: re-processing information for discovery and validation","authors":"R. Yeung, E. Capobianco","doi":"10.21037/JMAI.2019.03.01","DOIUrl":null,"url":null,"abstract":"A lot has been already said about the emerging role of big data in health and disease. Large scale data efforts are increasingly being undertaken in response to the advent of Personalized and Precision Medicine and in association with both the “omics revolution” and the Electronic Health Records centrality. big data have demonstrated that their complex characteristics bring both strength factors and bottlenecks to research problems widely identified, analyzed and reviewed across many sectors of medicine and public health. As the most significant feature of big data is “variety”, and this implies heterogeneity, our knowledge in complex disease contexts may substantially benefit from the fusion of different data types when a major role is assigned to harmonization and interoperability strategies. We discuss of an example, diabetes.","PeriodicalId":73815,"journal":{"name":"Journal of medical artificial intelligence","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.21037/JMAI.2019.03.01","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of medical artificial intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/JMAI.2019.03.01","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

A lot has been already said about the emerging role of big data in health and disease. Large scale data efforts are increasingly being undertaken in response to the advent of Personalized and Precision Medicine and in association with both the “omics revolution” and the Electronic Health Records centrality. big data have demonstrated that their complex characteristics bring both strength factors and bottlenecks to research problems widely identified, analyzed and reviewed across many sectors of medicine and public health. As the most significant feature of big data is “variety”, and this implies heterogeneity, our knowledge in complex disease contexts may substantially benefit from the fusion of different data types when a major role is assigned to harmonization and interoperability strategies. We discuss of an example, diabetes.
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
健康和疾病中的大数据:为发现和验证而重新处理信息
关于大数据在健康和疾病领域的新兴作用,人们已经说了很多。为了应对个性化和精准医疗的出现,以及与“组学革命”和电子健康记录中心相关的大规模数据工作正在越来越多地进行。大数据已经证明,其复杂的特性给医学和公共卫生的许多部门广泛识别、分析和审查的研究问题带来了优势因素和瓶颈。由于大数据最显著的特征是“多样性”,这意味着异质性,当协调和互操作性策略发挥主要作用时,我们在复杂疾病背景下的知识可能会从不同数据类型的融合中受益匪浅。我们讨论一个例子,糖尿病。
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
CiteScore
2.30
自引率
0.00%
发文量
0
期刊最新文献
Artificial intelligence in periodontology and implantology—a narrative review Exploring the capabilities and limitations of large language models in nuclear medicine knowledge with primary focus on GPT-3.5, GPT-4 and Google Bard Hybrid artificial intelligence outcome prediction using features extraction from stress perfusion cardiac magnetic resonance images and electronic health records Analysis of factors influencing maternal mortality and newborn health—a machine learning approach Efficient glioma grade prediction using learned features extracted from convolutional neural networks
×
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