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多尺度异步相关性和2D卷积自编码器用于青少年健康风险预测,fMRI数据有限

Di Gao1, Guanghao Yang1, Jiarun Shen1

  • 1School of Physical Education, China University of Mining & Technology (Beijing), Beijing, China.

Frontiers in computational neuroscience
|October 30, 2024
PubMed
概括

本研究引入了使用fMRI数据进行青少年健康风险评估的深度学习框架. 这种新方法显著提高了对心理和行为健康风险的预测准确度.

关键词:
青春期 青春期 青春期行为健康风险 行为健康风险卷积式自动编码器的自动编码器深度学习是一种深度学习.功能性磁共振成像技术 功能性磁共振成像技术评估健康风险 评估健康风险

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