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.
It compares measured and model-reconstructed HRV waveforms in three test cases (a, b, c), with corresponding MAE, MSE, Pearson correlation (r), and DTW values highlighted
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.IV 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.