A CNN-GRU model reconstructs pediatric heart rate variability waveforms directly from BOLD-fMRI, with an 8% accuracy gain when dynamic connectivity and white matter brain regions are included.
Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects,
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Direct Estimation of Pediatric Heart Rate Variability from BOLD-fMRI: A Machine Learning Approach Using Dynamic Connectivity
A CNN-GRU model reconstructs pediatric heart rate variability waveforms directly from BOLD-fMRI, with an 8% accuracy gain when dynamic connectivity and white matter brain regions are included.