Machine Learning and Brain Imaging: Opportunities and Challenges

被引：4
|
作者：
Paulus, Martin P. [1 ,2 ]
Kuplicki, Rayus [1 ,2 ]
Yeh, Hung-Wen [1 ,3 ]
机构：
[1] Laureate Inst Brain Res, Tulsa, OK 74136 USA
[2] Univ Tulsa, Dept Community Med, Tulsa, OK 74104 USA
[3] Childrens Mercy Hosp, Hlth Serv & Outcomes Res, Kansas City, MO 64108 USA
来源：
TRENDS IN NEUROSCIENCES | 2019年 / 42卷 / 10期
关键词：
D O I：
10.1016/j.tins.2019.07.007
中图分类号：
Q189 [神经科学];
学科分类号：
071006 ;
摘要：
Machine learning approaches may provide ways to link brain activation patterns to behavior at an individual-subject level. Using a comparative performance analysis, Jollans and colleagues (Neuroimage, 2019) highlight in a recent paper key considerations when applying machine learning algorithms to neuroimaging data.
引用
收藏
页码：659 / 661
页数：4
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