Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

Y. Park, Narae Lee, S. Ahn, Jong-Hee Chang, Seung-Koo Lee
{"title":"Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications","authors":"Y. Park, Narae Lee, S. Ahn, Jong-Hee Chang, Seung-Koo Lee","doi":"10.13104/imri.2021.25.4.266","DOIUrl":null,"url":null,"abstract":"Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.","PeriodicalId":73505,"journal":{"name":"Investigative magnetic resonance imaging","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Investigative magnetic resonance imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13104/imri.2021.25.4.266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.
放射组学和深度学习在脑转移中的应用:当前趋势和未来应用路线图
放射组学和深度学习(DL)的进展具有巨大的潜力,可以成为治疗脑转移患者的精准医学的前沿。放射组学和DL可以通过实现准确的诊断、促进分子标记的识别、提供准确的预后和监测治疗反应来帮助临床决策。在这篇综述中,我们总结了放射组学和DL治疗脑转移瘤的临床背景、未满足的需求和研究现状。放射组学和DL在脑转移中的前景、缺陷和未来路线图也得到了解决。
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
CiteScore
1.20
自引率
0.00%
发文量
0
×
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