FetalSleepNet achieves 86.6% accuracy in fetal sleep stage classification from ovine EEG by fine-tuning an adult model with spectral equalisation domain adaptation, outperforming baselines as the first such deep learning system.
Fetal autonomic brain age scores, segmented heart rate variability analysis, and traditional short term variability
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FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep Stage Classification
FetalSleepNet achieves 86.6% accuracy in fetal sleep stage classification from ovine EEG by fine-tuning an adult model with spectral equalisation domain adaptation, outperforming baselines as the first such deep learning system.