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在多站点fMRI研究中克服站点变性:用于增强机器学习模型的自动编码框架

Fahad Almuqhim1,2, Fahad Saeed3

  • 1Knight Foundation School of Computing and Information Sciences (KFSCIS), Florida International University, Miami, FL, USA.

Neuroinformatics
|September 2, 2025
PubMed
概括

自动编码器有效地协调多站点功能磁共振成像 (fMRI) 数据,提高机器学习模型的概括性. 这种新的方法减少了特定地点的变化和数据泄露,提高了临床应用的可靠性.

关键词:
进行分类数据协调深度学习一个FMRI多个站点

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