Brain Age Estimation Using UK Biobank Data: Methodologies and Outcomes

Q4 Medicine
Ahmed M. A. Salih
{"title":"Brain Age Estimation Using UK Biobank Data: Methodologies and Outcomes","authors":"Ahmed M. A. Salih","doi":"10.2174/18744400-v13-e221007-2020-5","DOIUrl":null,"url":null,"abstract":"Brain age estimation has received much attention from neurologists and researchers in recent years. It can be used to track cognition development and monitoring brain diseases progress throughout life span for both healthy and patient’s people. Different methods and data have been used to predict age of brain based on research objective. Supervised ma-chine learning methods are used to estimate brain age as a regression problem. UK Biobank is a large cohort prospective that gathered health related data about 500, 000 British aged between 40 and 69 since 2006. Many studies have used UK biobank data to estimate brain age. We discuss their methods, data used and the objective of these studies. We also highlight the differences among them despite the use of same data and for the same purpose.","PeriodicalId":37431,"journal":{"name":"Open Neuroimaging Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Neuroimaging Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/18744400-v13-e221007-2020-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Brain age estimation has received much attention from neurologists and researchers in recent years. It can be used to track cognition development and monitoring brain diseases progress throughout life span for both healthy and patient’s people. Different methods and data have been used to predict age of brain based on research objective. Supervised ma-chine learning methods are used to estimate brain age as a regression problem. UK Biobank is a large cohort prospective that gathered health related data about 500, 000 British aged between 40 and 69 since 2006. Many studies have used UK biobank data to estimate brain age. We discuss their methods, data used and the objective of these studies. We also highlight the differences among them despite the use of same data and for the same purpose.
利用英国生物库数据估计脑年龄:方法和结果
近年来,脑年龄估计受到神经学家和研究人员的广泛关注。它可以用于跟踪健康人和患者的认知发展,并在整个生命周期内监测脑疾病的进展。基于研究目的,已经使用了不同的方法和数据来预测大脑的年龄。有监督的机器学习方法被用来将大脑年龄估计为一个回归问题。英国生物银行是一个大型前瞻性队列,自2006年以来收集了约50万名年龄在40岁至69岁之间的英国人的健康相关数据。许多研究使用英国生物库数据来估计大脑年龄。我们讨论了他们的方法、使用的数据和这些研究的目的。我们还强调了它们之间的差异,尽管使用了相同的数据并用于相同的目的。
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 求助全文
来源期刊
Open Neuroimaging Journal
Open Neuroimaging Journal Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
0.70
自引率
0.00%
发文量
3
期刊介绍: The Open Neuroimaging Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, and letters in all important areas of brain function, structure and organization including neuroimaging, neuroradiology, analysis methods, functional MRI acquisition and physics, brain mapping, macroscopic level of brain organization, computational modeling and analysis, structure-function and brain-behavior relationships, anatomy and physiology, psychiatric diseases and disorders of the nervous system, use of imaging to the understanding of brain pathology and brain abnormalities, cognition and aging, social neuroscience, sensorimotor processing, communication and learning.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信